BASELINE REPORT
DRG LEARNING, EVALUATION, AND RESEARCH ACTIVITY:
Impact Evaluation of USAID/Peru’s “La Lucha Contra la Influencia de los Intereses Ilegales en Los Procesos Políticos del Perú”
DECEMBER 2015
Contract No. GS-10F-0033M/AID-OAA-M-13-00013 This publication was produced for review by the United States Agency for International Development. It was prepared by NORC at the University of Chicago. The authors’ views expressed in this publication do not necessarily reflect the views of the United States Agency for International Development or the United States Government.
DRG LEARNING, EVALUATION, AND RESEARCH ACTIVITY: Impact Evaluation of USAID/Peru’s “La Lucha Contra la Influencia de los Intereses Ilegales en Los Procesos Políticos del Perú”
Baseline Report (December 2015)
Prepared under Contract No.: GS-10F-0033M / AID-OAA-M-13-00013, Tasking N 016
Submitted to: USAID/Peru
Submitted by: Aaron Abbarno, Democracy Fellow DRG-L, Principal Investigator Nicole Bonoff, Democracy Fellow DRG-L, Principal Investigator Noam Lupu, NORC Principal Investigator (University of Wisconsin-Madison) David Greenwood-Sanchez, NORC Graduate Research Assistant (University of Wisconsin-Madison)
Contractor: NORC at the University of Chicago Attention: Renée Hendley Bethesda, MD 20814 Tel: 301- 634-9489; E-mail: [email protected]
DISCLAIMER The authors’ views expressed in this publication do not necessarily reflect the views of the United States Agency for International Development or the United States Government. IMPACT EVALUATION OF USAID/PERU’S LUCHA PROGRAM
CONTENTS
Acronyms ...... ii
Tables ...... iii
Figures ...... iii
Executive Summary ...... 1
1. Introduction ...... 2
2. Methodology ...... 5
3. Questionnaire Development and Tablet Programming ...... 8
4. Data Collection and Quality Control ...... 8
5. Data Cleaning ...... 9
6. Key Findings ...... 9
7. Conclusions ...... 21
Annex A, Concept Note ...... 23
Annex B, Survey Instrument ...... 35
Annex C, Surveyed Localities ...... 60
Annex D, Balance Report ...... 62
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ACRONYMS DRG Democracy, Human Rights, and Governance DRG-LER DRG Learning, Evaluation, and Research Activity IDEA International Institute for Democracy and Electoral Assistance IE Impact Evaluation IPSOS Ipsos IRB Institutional Review Board JNE Jurado Nacional de Elecciones LER Learning, Evaluation, and Research Lucha La lucha contra la influencia de los intereses ilegales en los procesos políticos del Perú NORC National Opinion Research Center (NORC at the University of Chicago) ONPE Officina Nacional de Procesos Electorales PAPI Paper-and-Pencil Interviewing USAID United States Agency for International Development USD United States Dollar ($)
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TABLES
Table 1 Impact Evaluation Research Design ...... 6 Table 2 Gender Balance ...... 10 Table 3 Educational Attainment ...... 10 Table 4 Household Assets ...... 12 Table 5 Perceptions of Government and the Economy ...... 13 Table 6 Perceptions of Economic Change ...... 13 Table 7 Political Knowledge ...... 14 Table 8 Correlates of Experiences with Corruption ...... 17 Table 9 Tradeoffs in Government Intervention ...... 19
FIGURES
Figure 1 Monthly Household Income ...... 11 Figure 2 Subjective Respondent Wealth ...... 12 Figure 3 Overall Perceptions of Corruption ...... 15 Figure 4 Perceptions of Specific Cases of Corruption ...... 15 Figure 5 Experiences with Bribery, by class ...... 16 Figure 6 Experiences with Clientelism, by class ...... 17 Figure 7 Support for Government Intervention to Fight Corruption ...... 18 Figure 8 Tradeoff between Fighting Corruption and Promoting the Economy, by class ...... 19 Figure 9 Political priorities, by class ...... 20 Figure 10 Tradeoff between Corruption and Economy in a Survey Experiment ...... 21
BASELINE REPORT | iii IMPACT EVALUATION OF USAID/PERU’S LUCHA PROGRAM EXECUTIVE SUMMARY This report presents the findings of the baseline survey for the Impact Evaluation (IE) of La Lucha Contra la Influencia de los Intereses Ilegales en los Procesos Políticos del Perú (hereafter referred to as Lucha Program). The Lucha Program aims to enhance the capacity of Peruvian civil society and state institutions to monitor the selection of candidates for inclusion on party lists and their campaign finance sources to reduce the influence of illegal interests – especially drug trafficking, illegal mining and illegal logging – over elections and political processes in Peru.
This report first discusses the background of corruption in Peruvian politics and then presents the Impact Evaluation (IE) design, which consists of a randomized household-level information dissemination campaign. The methodology of the IE is presented including a description of the sampling of villages along with information about the baseline questionnaire development and data cleaning.
Results are presented from a 1000 person household survey that took place in the Loreto and Ucayali regions of Peru during Summer 2015. The data suggest that an overwhelming majority of respondents think public employees and officials abuse their power in office, in all forms of public office. Although respondents in the sample generally think that public officials engage in corruption, many seem uninformed about particular politicians’ corrupt practices.
Around 14 percent of respondents report being asked to pay a bribe in the last 12 months, likely an underestimate, with the majority reporting these bribes going to police officers. Additionally, wealthier citizens are much more likely to be asked to pay a bribe by a public official. Conversely, poorer citizens are more likely to have received material assistance from political candidates, also known as clientelism, which is consistent with other scholarship. Individuals who were asked to pay a bribe have less confidence in political institutions, are more likely to think corruption is widespread, and feel less political efficacy. On the other hand, participation in clientelism seems to have none of these effects.
Citizens are broadly supportive of fighting corruption in both the public and private sectors. However, when forced to consider tradeoffs between policies for fighting corruption and economic growth, only 47 percent of respondents prioritize fighting corruption. Similarly, 46 percent of respondents agreed that public officials who improve the economy should be allowed to engage in corruption. Only 12 percent of respondents identified corruption as the main problem facing the country compared to 32 percent stating crime and security and 29 percent stating the economy. All of these results appear to be conditional on economic class, with poor respondents valuing economic growth over combating corruption more than rich respondents.
These findings suggest that anti-corruption may be seen as a “luxury,” something voters can only concern themselves with once they have reached a basic level of economic security. However, these findings provide a clear strategy for anti-corruption messaging. The Lucha Program may be able to convince voters they need not make the tradeoff between combating corruption and economic growth, and that citizens may choose candidates who are both honest and capable of creating good economic outcomes.
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1. INTRODUCTION This report presents findings from a baseline survey conducted by Principal Investigators from USAID’s Office of Learning, Evaluation, and Research (DRG- LER) and contracted through NORC at the University of Chicago as part of the Impact Evaluation (IE) of USAID/Peru’s program, La Lucha Contra la Influencia de los Intereses Ilegales en los Procesos Políticos del Perú (hereafter referred to as Lucha Program). The Lucha Program aims to enhance the capacity of Peruvian civil society and state institutions to monitor the selection of candidates for inclusion on party lists and their campaign finance sources to reduce the influence of illegal interests – especially drug trafficking, illegal mining and illegal logging – over elections and political processes in Peru.1 Lucha Program is a $1,930,000 project funded by USAID and implemented by the International Institute for Democracy and Electoral Assistance (IDEA) between September 2014 and April 2017.
BACKGROUND In recent years, high profile scandals have rocked Peru’s political establishment. Of three former presidents, two are under investigation for corruption and the third is incarcerated. In Congress, a number of members have been publicly linked with narco-trafficking and illegal mining. At the subnational level, the influence of illicit resources in political circles is widely acknowledged. Most recently, in the region of Ancash, Peru, there has been a rash of politically motivated killings allegedly spurred by corruption related to the influx of mining revenue.
While Peru has enjoyed three successive peaceful transfers of power since 2002, the country’s institutions and political systems are alarmingly weak. Problems include the absence of a cadre of professional civil servants, the frequent turnover of key officials at the national level, weak to non-existent political parties, personality/scandal-driven politics, widespread corruption, and weak institutional controls. In this context, politicians linked to illegal activities (mining, drug trafficking, logging), have relative freedom to pursue their particularized interests with a short- term horizon (reelection rates for members of Congress was 18 percent in the last elections), undermining good governance and reinforcing citizens’ lack of faith in democratic processes.
THEORY OF CHANGE Standard democratic theory predicts that when citizens know negative information about a candidate, they will be less likely to cast their vote for that candidate and this in turn deters politicians from engaging in illicit activities. The implication is that where elite corruption is rampant, it is because voters are either unaware of it, or they fail to understand the negative consequences of corruption. Providing information to voters about which politicians engage in corruption, or sensitizing voters to the negative consequences of corruption more broadly, should help voters
1 Hereafter “corruption” will be used to refer to these three specific interests.
BASELINE REPORT | 2 IMPACT EVALUATION OF USAID/PERU’S LUCHA PROGRAM hold politicians accountable for corruption and, in turn, deter elite corruption more generally. Similarly, the Lucha Program proposes that mobilizing citizen awareness of corruption and its consequences will help reduce the influence of illegal interests on Peruvian political processes. However, in practice, empirical evidence for this Theory of Change is mixed.
EVALUATION OBJECTIVES The purpose of the evaluation is to examine two complementary Lucha Program interventions that target informational deficits among Peruvian citizens making a voting decision. The first intervention is “social mobilization events,” or fairs. These fairs will be held in the weeks prior to the election in a randomly selected set of 20 communities in Loreto and Ucayali, the two target regions of the Lucha Program. Fairs will involve local artists and actors who will provide information about local candidates running for office as well as messages promoting the importance of electing clean politicians who are honest about their financial backing.
The second intervention, which will be co-created by the evaluation team and implementing partner IDEA International, is a set of household informational flyers that mirror the messages of the fairs. There will be three types of messages to understand how different messages related to political corruption affect attitudes and behaviors.
■ Informational: basic facts about political corruption ■ Consequentialist: specific costs associated with corruption (e.g., health consequences of illegal mining; environmental effects of logging; violence and security, etc.) ■ Normative: normative condemnation through the lens of democratic values/procedure
These three messages will help answer the primary research question about whether citizens simply lack information about corruption in the targeted regions, or if citizens are unmotivated by that information and require contextualizing messages to sensitize them to corruption as it relates to them. This IE is conducted through USAID’s Center of Excellence on Democracy, Human Rights and Governance (DRG Center) in Washington, D.C. The Lucha Program targets activities in the Peruvian regions of Loreto and Ucayali by providing residents with information about corruption in elections, specifically illegal campaign finances from illegal industries (mining, logging, and narcotrafficking).
This IE will test the hypothesis that “better-informed citizens are expected to be more likely to monitor and sanction politicians linked to corrupt practices.” In addition to measuring how information about this kind of political corruption affects citizen attitudes, this IE will attempt to address how different approaches to discussing the dangers of corrupt candidates as well as the mode by which people receive information affect people’s beliefs and political behaviors.
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BASELINE SURVEY OBJECTIVES As part of the IE, the baseline survey, of which this report analysis focuses, has three objectives. The first is to better understand citizens’ attitudes toward, perceptions of, and experiences with corruption. The second is to provide baseline estimates of indicators of these attitudes and preferences. The third is to identify baseline differences across the treatment and control groups that will be used to measure the impact of the project.
EVALUATION QUESTIONS The Lucha Program affords an opportunity to reexamine the assumed links between citizen information about corruption and democratic hygiene. Moreover, it provides a setting in which to investigate the political consequences of corruption at the local level, where corruption may be more visible but potentially less costly. Thus, there are several basic research questions at the core of this impact evaluation:
■ Does increasing the accuracy and availability of information about corrupt party/campaign practices lead to increased voter knowledge of, interest in, and preferences against illicit interests in Peruvian political processes? ■ What type of information (“message content”) and mode of delivery (“message platform”) – generate the most interest in, and the strongest sensitization to, the problem? ■ Can social mobilization events generate broader networks of interest in, and concern with, political corruption in Peru? ■ To what extent do voters rely on this information to evaluate candidates? ■ To what degree do voters base their vote on this information relative to more traditional determinants of vote choice, like candidate issue positions or perceived ability to deliver public goods? ■ Do voters scrutinize or punish candidates or parties in other ways – e.g. through casting “blank ballots” or by moving dishonest candidates down the list?2
Concrete answers to these questions will help enhance future Lucha Program and activity effectiveness. This IE design will allow the team to compare several varieties of messages about corruption and different modes of disseminating that information; it has the potential to adjudicate between disparate findings in the scholarly literature and also deliver concrete lessons to USAID/Peru and responsible government institutions like Oficina Nacional de Procesos Electorales (ONPE) and Jurado Nacional de Elecctiones (JNE) about how best to equip citizens to fight illicit interests in Peruvian politics.
2 Assuming that preference voting is not only for the National Congress.
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2. METHODOLOGY IMPACT EVALUATION DESIGN The IE design of USAID/Peru’s Lucha Program uses a household-based randomization strategy to best attribute outcomes of interest to the program. The IE team made this decision was made because of the relatively small geographic area where the Lucha Program is being implemented and the lack of geographically- located sub-constituency precincts, which limits outcomes of interest to the individual level.
By using household randomization of information as an identification strategy, the IE is better able to accurately measure outcomes given an environment where many political activities are occurring in a relatively small area. By assigning different treatment groups at the household level, the project increases the potential sample size to allow for the creation of a valid counterfactual control group through statistical sampling.
Not only is it possible to separate and identify the independent effects of different message content, but it is also possible to analyze the relative effectiveness of delivering this information face-to-face through neighborhood canvassing vs. delivering this information through social mobilization activities.
Both the different informational messages and the social mobilization event will be randomized, the former at the household level and the latter at the community level. The randomized promotion strategy for the mobilization events address this somewhat by effectively increasing the salience of the event for certain households. However, through work with implementing partner IDEA, the impact evaluation design uses a quasi-experimental matching strategy to assign one member of a pair of similar towns to receive the mobilization event, 20 communities in total. This will help address the urban bias of the events where politics might differ considerably from more rural communities.
Table 1, Impact Evaluation Research Design, outlines the different types of households in the IE design. Through random assignment of communities and households into these groups, the IE team is able to address several pertinent questions. First, the team can measure what type of message generates the most interest in, and sensitization to, the issues associated with political corruption. In other words, which type of information matters most for citizens outcomes, either in the presence of a mobilization event or not? This can be done by comparing C1+C2
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Table 1 Impact Evaluation Research Design Household message type Community with fair Community with no fair Control C1 C2 Informational message T1 T4 Consequentialist message T2 T5 Normative message T3 T6
This approach also allows the IE team to study what type of information delivery – “message platform” – generates the most interest in, and sensitization to, the issues associated with political corruption. For example, does the social mobilization event promote knowledge and behavioral change in citizens? The IE team can answer this question by comparing C1+T1+T2+T3 with C2+T4+T5+T6. Does the mode of engagement (flyer versus fair) affect citizen outcomes? The IE team can study this question by comparing T1+T2+T3 vs. T4+T5+T6. Finally, the IE design can address the question of spillover effects and the saliency of social mobilization events in urbanized areas through the sampling strategy where enough households are brought into the experiment that are different distances from the site of the event, with distance serving as a proxy for the likelihood of attending an event given no outside encouragement to attend.
IMPACT EVALUATION IMPLEMENTATION The IE design includes three waves of data collection and dissemination of treatments. The first wave, which forms the basis of this report, is the baseline data collection which was administered between June 19 and July 23, 2015. In this wave, 1,000 interviews were conducted, 25 in each of the 40 sampled communities.
The second wave of data collection will take place late February 2016. During that wave which is a panel of this first wave, respondents will be asked a short survey and then be provided with the appropriate flyer if they are to receive one. After this data collection activity, the fairs will be held in March 2016 and the election will occur on April 10, 2016. Immediately after the election, a third and final wave of data collection will take place, also in panel, to measure any changes that can be attributed to the Lucha Program activities.
SELECTION OF LOCALITIES A matching procedure was used to select the localities for this impact evaluation. In collaboration with local survey firm IPSOS, the IE team identified all of the localities in Loreto and Ucayali that, according to Peru’s 2007 census, would have sufficient households (rural areas) or population (urban areas) to sustain the number of cases needed per locality. Localities that were within a reasonable distance from the regional capitals and reasonably accessible by car or boat (that is, localities only accessible by plane were excluded) were also selected. These localities were then matched into pairs using propensity score matching on the basis of these demographic characteristics: population; number of households; urbanization rate;
BASELINE REPORT | 6 IMPACT EVALUATION OF USAID/PERU’S LUCHA PROGRAM and literacy rate. Within each region, 20 pairs of localities were then randomly selected (see Annex C, Surveyed Localities).
Wave 1 of the survey involved the survey team administering face to face tablet surveys to individuals in 25 households in each of these 40 localities. Waves 2 and 3 of the panel survey will involve administering 50 interviews in each locality. Within each matched pair, one locality was subsequently randomly selected to receive a community fair in March 2016.
HOUSEHOLD SAMPLING AND SURVEY ADMINISTRATION The target population for the baseline survey included adult Peruvian citizens in the 40 communities in Loreto and Ucayali selected for the study (see Annex C, Surveyed Localities). Within the urban localities, local data collection teams from IPSOS-Peru randomly selected a block, a corner on that block, and walked in a clockwise or counterclockwise direction, and then proceeded to every third household.
Within rural areas, the locality was split into four quadrants. The enumeration teams randomly selected one quadrant. Since blocks could not be identified, enumeration teams identified groups of houses built close to each other. A random group was selected and enumerators were instructed to conduct a random walk until they completed an interview. At that point, enumerators moved to a different, distant grouping of houses and conducted a new random walk.
Within households, gender and age quotas were used in the selection process. Enumerators asked whether an individual of a certain gender and age range lived in that household and, if so, selected that individual for the interview. If more than one individual in a household met the criteria, the enumerator selected the one with the most recent birthday.
SURVEY ADMINISTRATION CHALLENGES Two of the 40 selected municipalities needed to be replaced during the fieldwork due to unforeseen circumstances:
■ In Loreto, the village of Grau in the Nauta district became flooded and lost access to electricity. Residents left their homes and moved temporarily to nearby localities. Local data collection firm IPSOS suggested replacing this locality with the demographically similar village of 13 de Febrero in the San Juan Bautista district of Loreto. ■ In Ucayali, the village of 2 de Mayo in the Yarinacocha district turned out only to have 25 dwellings, in contrast to the over 100 indicated by the 2007 census. IPSOS suggested replacing this locality with the demographically similar locality of San Lorenzo, which is in the same district.
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3. QUESTIONNAIRE DEVELOPMENT AND TABLET PROGRAMMING To meet the objectives of the study, the survey instrument was designed to measure the following key areas:
■ Perceptions of corruption across multiple levels of government and types of government actors; ■ Attitudes about government interventions regarding political corruption; ■ Personal experiences with corruption (e.g., bribes, clientelism); ■ Political preferences; ■ Political characteristics including partisanship, participation, interest, and knowledge; and, ■ Demographic characteristics including socioeconomic status, media consumption, education, and civic engagement.
The IE team designed the baseline surveys using the latest knowledge on question and survey design as they relate to corrupt government practices. Some questions were modified in conjunction with local data collection partner IPSOS to reflect local realities. The IE team also solicited feedback on the survey instrument from the USAID Mission and the Lucha Program implementer, IDEA International.
Each participant was required to provide informed consent prior to taking the survey and after having been read the statement of purpose, the content of the survey, any risks or benefits, and the time commitment. Participants were assured their participation was voluntary (they could withdraw from the survey at any point and refuse to answer any questions they did not want to answer), and that their answers would be kept confidential.
NORC’s Institutional Review Board (IRB) reviewed and approved the survey instrument and survey administration protocols in May 2015.
4. DATA COLLECTION AND QUALITY CONTROL The IE team took several steps to ensure data quality, including:
■ Programming the questionnaire into the SurveyToGo tablet platform. This eliminated the slow and tedious data-entry process required with traditional Paper-and-Pencil Interviewing (PAPI) questionnaires which have a greater likelihood of introducing increased human error; ■ The use of tablet-based electronic data capture to enter responses by the interviewer and regular uploading of the data to the cloud ensured that the data
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was subject to regular diagnostics by local data collection subcontractor IPSOS and the IE team; and, ■ The IE team, IPSOS management, and the field teams were in regular contact to address any challenges that arose during fieldwork.
5. DATA CLEANING Data collected for the baseline survey required only a minimal amount of cleaning. The IE team attributes this to (a) its oversight of the SurveyToGo programming, including a line-by-line review; (b) its use of a pilot survey to find and correct questionnaire errors prior to the baseline survey; and (c) a well-trained and highly- effective group of IPSOS-Peru interviewers.
The IE team followed a set of procedures to avoid and minimize data errors. Upon receiving the baseline dataset, the IE team conducted a detailed inspection of the data for irregularities. Some errors were discovered regarding the inclusion of “other” responses; IPSOS was notified immediately, and they promptly corrected the errors, producing the final dataset used to produce analysis for this report.
Additional cleaning by the IE team can be grouped into two types. First, missing values were removed on a case-by-case basis for the purposes of the analysis, and following standard practice. Second, an index of political knowledge was created by summing each respondent’s correct responses to a set of pre-determined “knowledge” questions (see Table 6.6). All of the IE team’s data cleaning and preparation decisions are recorded and available as STATA do-files.
6. KEY FINDINGS This section provides a review of central findings from the household baseline survey. The presentation is organized into four sections − descriptive characteristics of respondents; citizens’ perception of corruption; citizens’ experiences with corruption; and citizens’ attitudes about corruption − the latter three correspond to each of the IE’s outcomes of interest.
RESPONDENT CHARACTERISTICS Respondent Gender The household survey was administered using quotas to achieve gender balance among the 1,000 respondents. Table 2, Gender Balance, shows the methodology for selection during the survey was successful in this respect. Gender balance is near 50/50 within the entire sample as well as within each of the two regions of Loreto and Ucayali. To assess the representativeness of the sample, the IE team compared gender balance results from the survey with data collected in Peru’s 2007
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census within Loreto and Ucayali. Indeed, the survey results match very closely with census data.
Table 2 Gender Balance Loreto Ucayali Total 2007 Census Male 249 246 495 51% Female 251 254 505 49% Total Respondents 500 500 1000 --
Respondent Age The average age of respondents in the sample is 37 years, and ranges from 18 to 70. Age differences are negligible across the two regions. However, male respondents are slightly older, with an average age of 38.6 years of age compared to 36.6 years of age for female respondents.
Respondent Education The vast majority of respondents have received some level of formal education. Table 3, Educational Attainment shows that 83% of respondents have completed, at a minimum, primary education; approximately half (49%) of the respondents completed secondary school; and another 21% received at least some secondary education without finishing. Approximately 17% of respondents completed non- university post-secondary degree, and 4% completed a university degree. Male respondents in our survey hold higher rates of educational attainment at each level of education, with differences as high as 16% points in the case of secondary education. Comparing these results to the 2007 census suggests that survey respondents have a slightly higher rate of post-secondary education. However, the educational attainment rates in this sample appear quite normal.
Table 3 Educational Attainment Men (%) Women (%) Total (%) 2007 Census Primary 87 79 83 87 Secondary 57 41 49 47 Post-secondary 20 13 17 10 University 5 3 4 4
Respondent Household Income In terms of household income, the data shows the average monthly household income is 661-860 Peruvian Soles (equivalent to USD 208-271 per month).3 The modal response, however, is 461 to 660 Peruvian Soles per month (equivalent to USD 145-208), reflecting the data are skewed right. Figure 1, Monthly Household Income, presents the full income distribution. Approximately 75% of respondents report household incomes at or below 1060 Peruvian Soles per month (equivalent to about US$335 per month). As a point of comparison, the current minimum wage in
3 At the time of the survey, the exchange rate was 3.17 Peruvian Nuevo Soles per USD.
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Peru is 750 soles per month. As would be expected for these regions, these figures suggest respondents are relatively poor by national standards.
Figure 1 Monthly Household Income
In addition to household income level, the survey asked respondents to place themselves on a 10-point scale where 1 represents the poorest Peruvians and 10 represents the richest. Figure 2, Subjective Respondent Wealth below shows results which suggest respondents generally perceive themselves to be very poor. In fact, 39% placed themselves in the lowest category, and less than 1 percent of respondents placed themselves in any of the categories within the upper half of the distribution.
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Figure 2 Subjective Respondent Wealth
Household Assets As illustrated in Table 4, Household Assets, the majority of respondents have televisions, cell phones, and safe drinking water. Notable, however, respondents have very low rates of internet service – just 7% – within their homes. Motorized transportation is also noticeably low; only 2% of households have a car, and just 30% have a motorcycle. A comparison of these ownership rates with the 2007 census data suggests respondents have higher rates of asset ownership than is typical. However, this might also be a product of the census data being outdated at the time of the survey.
Table 4 Household Assets Asset % with Asset 2007 Census Television 77 48 Cellular phone 68 24 Potable water inside house 50 -- Refrigerator 41 20 Motorcycle 30 -- Bathroom 26 -- Flat-screen television 23 -- Landline phone 13 20 Computer 12 7 Washing machine 11 6 Internet service 7 2 Microwave 7 -- Car 2 --
Perceptions of the Government and the Economy To better understand political attitudes within the target population, the survey asked respondents a series of questions asking them to evaluate the government and the
BASELINE REPORT | 12 IMPACT EVALUATION OF USAID/PERU’S LUCHA PROGRAM economy. Data summarized in Table 5, Perceptions of Government and the Economy, show that despite Peru’s strong national economic growth in recent years, respondents hold mixed, but moderate, views about government performance. The most noticeable trend is that across all the factors, virtually none of the respondents assess performance as very good. Second, for each factor, the number of respondents who view performance as bad is similar to those who view it as good, with strong clustering in the middle. Third, respondents’ views are less moderate when assessing the performance of specific political leaders: in the evaluations of President Ollanta Humala and the respondent’s mayor, 11% and 12% of respondents view their performance as very bad.
Table 5 Perceptions of Government and the Economy Performance of Personal Performance Current economic President economic of mayor (%) situation in Peru (%) Humala (%) situation (%) Very Bad 11 12 5 4 Bad 22 29 22 18 Average 48 35 53 59 Good 18 23 19 19 Very Good 1 3 1 1
The survey asked respondents about their perceptions of changes in the national economy and their own personal economic situation. Table 6, Perceptions of Economic Change, shows that approximately half of the respondents have not noticed any change in economic conditions, either nationally or in their own locations. The other half is split between better and worse, with very few respondents taking a position an extreme view.
Table 6 Perceptions of Economic Change Personal economic National economy (%) situation (%) Much Worse 3 3 Worse 24 20 Neither worse nor better 50 47 Better 23 27 Much Better 0 3
Another key area of interest within this survey concerns the level of respondents’ political knowledge. Prior political knowledge may condition the effects of the interventions in this project. The IE team measure political knowledge in two ways. First, respondents were asked to answer a series of four questions regarding local, national, and international politics in Peru, specifically: (1) the year in which the current Peruvian Constitution was enacted; (2) the name of Brazil’s current president; (3) the cabinet position of Alonso Segura Vasi; (4) the number of seats in Peru’s Chamber of Deputies; and, (5) if regional president has been investigated for corruption. Following standard practice in the field, the IE team summed the total
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correct answers for each respondent to create a score of political knowledge. Second, each enumerator was also asked upon completing each survey to assess the level of political knowledge of the respondent. Both measures are complementary, and allow the IE team to assess the political knowledge of this sample of respondents. The distribution of respondents is reported in Table 7, Political Knowledge.
Although the IE team has no prior data available on these questions to compare results, it is still able to draw some conclusions. As Table 7, Political Knowledge, shows, roughly a quarter of respondents fell in the very low category of political knowledge. In the next two categories – low and average levels of political knowledge – the two measures differ, but 60 percent of respondents fall into these two categories combined regardless of the type of measure. Finally, roughly 15 percent of respondents fall into the two highest levels of political knowledge – high and very high.
Table 7 Political Knowledge Knowledge scale Factual questions (%) Enumerator Evaluation (%) Very low (0 correct) 27 19 Low (1 correct) 42 29 Average (2 correct) 18 37 High (3 correct) 9 13 Very high (4-5 correct) 4 2
PERCEPTIONS OF CORRUPTION The data suggests that among the sampled respondents, there is an overwhelming perception that corruption pervades all levels of politics, which is consistent, in many ways, with political reality in Peru. The survey asked respondents whether different types of political actors and government personnel use their positions for personal gain. As is illustrated in Figure 3, Overall Perceptions of Corruption, in the best case – public employees in the health sector – 75% of respondents thought they did. In the worst case – the police – that rate went up to just over 91%. Data suggest that an overwhelming majority of respondents think public employees and officials abuse their power in office.4
4 These proportions are among only the randomly assigned half of the sample who were not asked about their own experiences with corruption just prior to this set of questions.
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Figure 3 Overall Perceptions of Corruption
Although data suggest respondents generally perceive a high level of corruption in general, they perceive quite a bit less corruption in specific cases. The survey asked respondents whether their current regional president of Loreto and Ucayali – Fernando Meléndez Celiz and Gambini Rupay, respectively – has been investigated for corruption. Both regional presidents have recently been investigated, although the case of the Ucayali president received more national media attention. Figure 4, Perceptions of Specific Cases of Corruption, shows a vast majority of Ucayali residents are aware of this investigation. But fully a quarter of Ucayali respondents indicate they are not aware of corruption charges against their regional president. In Loreto, nearly half of the sample reported being unaware of this particular case. Although respondents in the sample generally think that public officials engage in corruption, many seem uninformed about particular politicians’ corrupt practices.
Figure 4 Perceptions of Specific Cases of Corruption
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EXPERIENCE WITH CORRUPTION The second citizen outcome measured by the survey is respondents’ experiences with corruption. The IE team explored two possible ways in which individuals might come into contact with political corruption: (1) paying bribes to public officials; and (2) selling their vote to parties or political candidates.
Regarding bribery, respondents were asked directly whether they had been asked by a public official to pay a bribe in the last 12 months. Figure 5, Experience with Bribery, shows, 14% of respondents said they had been asked to pay a bribe in that time period. Since bribery is illegal, this may be an underestimate of the actual level of bribe-paying that takes place. But it gives us a lower bound on citizens’ experiences with this type of corruption. Note that while 14% seems like a small number, this only measures experiences in the last 12 months (under the assumption that recall beyond this is unreliable). Compounded over time, this means many citizens are asked by public officials to pay bribes.
Figure 5 Experiences with Bribery, by class
Of those respondents reporting they had been asked to pay a bribe, 77% reported they were asked to do so by police. That is, the vast majority of bribe requests from public officials come from police officers.
Figure 5 also shows these experiences with corruption are disproportionately distributed across socioeconomic groups (as a measure of household wealth). The rate at which the wealthiest quintile of respondents is asked to pay a bribe is twice the average, whereas the rate for the poorest quintile is less than half the average. In other words, the rich are much more likely to be asked to pay a bribe by a public official. It is perhaps unsurprising that public officials looking for a bribe are more likely to seek one from those who have more means to pay.
They IE team also examine individual respondents’ experience with clientelism. They survey asked individuals directly whether they had, in the prior 12 months, received
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“material assistance like food, clothing, or personal favors from some political candidate or representative.” Figure 6, Experiences with Clientelism, by class, shows 9% of respondents report they received goods or favors from a politician in the prior 12 months. Again, Figure 6.6 finds these experiences disproportionately distributed among social class, except that the poorest quintile of respondents is more likely to participate in clientelism and the richest less likely. That politicians seem to target poorer voters is consistent with scholarship on clientelism.
Figure 6 Experiences with Clientelism, by class
These reported experiences with corruption affect how citizens think about corruption more generally. Table 8, Correlates of Experiences with Corruption, shows individuals who were asked to pay a bribe have less confidence in political institutions,5 are more likely to think corruption is widespread, and feel less political efficacy. On the other hand, participation in clientelism seems to have none of these effects.
Table 8 Correlates of Experiences with Corruption Dependent variable Bribery Clientelism Confidence in political institutions -1.10* 1.26 (0.28) (0.78) Perception of corruption 21.79* 2.41 (3.28) (8.82) Political efficacy -2.67* -1.31 (1.22) (1.92) Standard errors in parentheses, * p<0.05 In sum, individual experiences with corruption are fairly widespread among the target population of the Lucha Program in the regions of Loreto and Ucayali. And these
5 This measure is an index that combines the level of confidence (on a scale of 1-10) in the National Congress, the judiciary, the political parties, the regional government, and the municipal government.
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experiences – being asked to pay a bribe, often by police officers – affect a host of political perceptions and attitudes that are important for democracy.
ATTITUDES TOWARD CORRUPTION The final outcome of interest is citizens’ attitudes about corruption. Here, the IE team examines how strongly citizens feel about the problems associated with corruption and the kinds of tradeoffs they are willing to make when it comes to fighting corruption.
To begin, respondents were asked general questions about if the government should do more to combat corruption. Figure 7, Support for Government Intervention to Fight Corruption, shows citizens in Loreto and Ucayali overwhelmingly support more government intervention in fighting corruption – regardless of whether it is corruption within the private sector, among public employees, or among politicians. In all three cases, 90% or more of respondents agree the government should do more. Of course, such responses may simply reflect social desirability. In the absence of any real costs or tradeoffs, it is not surprising to find such overwhelming support.
Figure 7 Support for Government Intervention to Fight Corruption
To examine some of these potential tradeoffs, the survey presented respondents to choose between two policy priorities and asked which one they would prioritize. As Table 9, Tradeoffs in Government Intervention, shows when respondents were forced to choose between protecting the environment and combating corruption, 74% chose to combat corruption. However, that proportion declines significantly when combating corruption is pitted against promoting economic growth. In that tradeoff, only 47% of respondents preferred combating corruption.
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Table 9 Tradeoffs in Government Intervention Issue Choice (%) Tradeoff 1 Protect the Environment 26 Combat Corruption 74 Tradeoff 2 Combat Corruption 47 Promote Economic Growth 53
Respondents were then presented with a similar forced choice, this time with questions that asked what kinds of politicians should be prosecuted for corrupt practices. Figure 8, Tradeoff between Fighting Corruption and Promoting the Economy, by class, represents how respondents answered to questions asking them if government should “always prosecute corrupt public officials, even if they help to improve the economy and provide employment” or “prosecute corrupt public officials only if they do not help to improve the economy and do not provide employment opportunities.” Despite the potential for social desirability in these responses, 46% of respondents chose the second statement – that is, public officials who improve the economy should be allowed to engage in corruption.
Figure 8 Tradeoff between Fighting Corruption and Promoting the Economy, by class
Figure 8 also shows that respondents’ willingness to make these tradeoffs between corruption and economic wellbeing are substantially conditioned by their own socioeconomic status. The wealthiest 20% of respondents (based on household wealth) was far less willing to allow corrupt politicians to evade prosecution when they perform well economically than the sample average and the poorest 20 percent of our sample.
These forced-choice questions are merely hypothetical exercises, but they nevertheless reflect a perceived reality. Nearly one third of respondents failed to
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disagree with the normative statement, “we must accept some corruption to promote economic growth.” The survey also asked respondents about the more specific and well-known corruption of Alberto Fujimori’s intelligence chief, Vladimiro Montesinos. In that case, an even larger 47% of respndents agreed with the statement, “The corruption employed by Vladimiro Montesinos during the presidency of Alberto Fujimori was justified because it improved the economy.”
Another way of examining citizens’ willingness to live with corruption is by the weight they place on corruption relative to other issues. The survey asked respondents what they thought is the most important issue facing the country. As Figure 9, Political Priorities, by class shows the modal issue for citizens in our sample is crime or personal security. After that, various types of economic issues – the economy in general, unemployment, or poverty – are primary concerns. Only 12% of respondents identified corruption as the main problem facing the country.6
Figure 9 Political priorities, by class
Again, these results are conditioned by the respondent’s socioeconomic situation. As Figure 9 shows, among the most affluent quintile of respondents, corruption is a higher priority and economic issues are lower priority. In contrast, economic issues are far more important for the poorest quintile of respondents than on average. And corruption for these poorer respondents is a far less pressing issue. Once again, citizens with greater economic needs are most willing to accept corruption in exchange for economic gains.
In all of these questions, however, respondents are asked directly or indirectly to make a conscious choice between fighting corruption and economic performance. A final way to examine the tradeoff citizens are willing to make is to do so implicitly with
6 Similarly, we asked respondents whether they agreed with the statement, “corruption impacts my income.” Only half of our sample agreed with that statement, suggesting that many respondents do not view corruption as personally costly.
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between-subjects comparisons rather than direct or indirect questions. The IE team did this by presenting respondents with a hypothetical incumbent candidate for mayor and randomly assigning whether that candidate (a) engaged in corruption; and/or (2) oversaw economic expansion. Then respondents were asked how likely they would be to vote for the candidate on a 1-4 scale.
Figure 10 Tradeoff between Corruption and Economy in a Survey Experiment
Unsurprisingly, as is illustrated in Figure 10, Tradeoff between Corruption and Economy in a Survey Experiment, the incumbent mayor who was said to have improved the economy consistently garnered more support than the incumbent mayor said to have overseen a worsening economy. Similarly unsurprising is that the mayor who was said to be corrupt consistently attracted less support than the one who was said not to be corrupt. What is striking, however, is even a mayor known to be corrupt is likely to get the vote of most sampled respondents, so long as she also improved the local economy. Again, the individuals in our sample were willing to look the other way on corruption so long as a politician delivers economic gains.
7. CONCLUSIONS Taken together, these baseline data offer both sobering advice for programming as well as optimism that the Lucha Program can help shape citizen’s attitudes about corruption. On the sobering side, the data suggests that citizens – particularly those worse off economically – are far more concerned with their economic well-being than with issues related to political corruption. This suggests that anti-corruption may be seen as a “luxury,” something voters can only concern themselves with once they have reached a basic level of economic security.
Optimistically, however, the data suggests three potential areas where the Lucha Program may be able to change public opinion and sway voter behavior:
■ First, the data suggests that while there is general consensus that public officials and politicians are corrupt, information about specific political actors is not as widespread. Information disseminated through the Lucha Program about specific
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candidates may, therefore, provide voters with new information that have the potential of changing voter behavior. ■ Second, the data suggests that voters are consistently willing to trade off fighting political corruption for economic gains. In some ways, this is a discouraging finding that provides an avenue of defense for corrupt political actors who can claim to have contributed to economic well-being. In other ways, however, this is an opportunity; the Lucha Program may be able to convince voters they need not make this tradeoff, and that they can choose candidates who are both honest and capable of creating good economic outcomes. ■ Finally, and relatedly, respondents in our sample – particularly the poorest – did not consider corruption to be a primary concern. There seems to be a great deal of room for the Lucha Program to make the corruption issue more salient and a great priority for a larger swath of the electorate in these regions.
In sum, the data suggests great potential for the Lucha Program to change public opinion regarding political corruption in Peru.
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ANNEX A, CONCEPT NOTE
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CONCEPT NOTE Impact Evaluation Concept Note La Lucha contra la influencia de los intereses ilegales en los procesos políticos del Perú DCHA/DRG/Learning 1. BACKGROUND AND RATIONALE In recent years, high profile scandals have rocked Peru’s political establishment. Of three former presidents, two are under investigation for corruption and the third is in jail. In Congress, a number of members have been publicly linked with narco-trafficking and illegal mining. At the sub-national level, the influence of illicit resources in political circles is widely acknowledged. Most recently, in the region of Ancash, there has been a rash of politically motivated killings allegedly spurred by corruption related to the influx of mining revenue.
While Peru has enjoyed three successive peaceful transfers of power since 2002, the country’s institutions and political systems are alarmingly weak. Problems include the absence of a cadre of professional civil servants, the frequent turnover of key officials at the national level, weak to non-existent political parties, personality/scandal-driven politics, widespread corruption, and weak institutional controls. In this context, politicians linked to illegal activities (mining, drug trafficking, logging), have relative freedom to pursue their particularized interests with a short-term horizon (re-election rates for members of Congress was 18 percent in the last elections), undermining good governance and reinforcing citizens’ lack of faith in democratic processes.
Given these risks, USAID/Peru’s program, La lucha contra la influencia de los intereses ilegales en los procesos politicos del Perú (hereafter, Lucha Program), aims to enhance the capacity of Peruvian civil society and state institutions to monitor and control the selection of candidates for inclusion on party lists, as well as their campaign finance sources and reduce the influence of illegal interests – especially drug trafficking, illegal mining and illegal logging – over elections and political processes in Peru. Hereafter “corruption” will be used to refer to these interests in the broadest sense.
USAID/Peru will initiate activities under the Lucha Program during the months prior to Peru’s April 2016 national elections. These activities comprise a multipronged messaging campaign to inform voters about the harm of corruption in politics generally, and about the status of specific candidates. These efforts are rooted in the theory that when citizens know negative information about a party or a candidate, they will be less likely to cast their vote for that candidate, and this in turn deters politicians from engaging in corruption.
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The Learning Team from USAID/Washington’s Center of Excellence in Democracy, Human Rights and Governance will design and carry out an evaluation of these activities’ impact on voters and electoral processes. Lessons learned from this IE will help enhance program and activity effectiveness. Lessons will also contribute to broader efforts to understand citizen attitudes toward corruption, to sensitize voters to the risks of illicit interests in political processes across the Andean region.
2. RESULTS FRAMEWORK Lucha Program’s primary objective is to “Reduce the influence of illegal interests on Peruvian electoral processes.” Its two principal intermediate results include equipping voters with the information and tools needed to better evaluate their candidates (Result 1), and enabling media and opinion leaders to influence the selection of trustworthy candidates (Result 2). Owing to the limited window of opportunity to program activities prior to the October 5, 2014 municipal elections, International IDEA will implement elements pertaining to Result 1 only. Likewise, the impact evaluation will address progress toward Result 1 and the “awareness campaign” (Activity 1.1) and “social mobilization events” (Activity 1.2) that should drive progress toward that result. The impact evaluation’s focus on messaging means the IE will also obliquely address Activities 1.3 and 1.4, which comprise the production of communication materials and web-based information platforms designed to augment public information about candidates prior to the election.
a. Inputs & Outputs International IDEA proposes several tools and activities for the pilot phase. These items aim to 1) increase the volume of accurate information regarding candidates’ biographies, levels of campaign spending, and sources of campaign finance; and 2) orient voters toward “best practices” in candidate selection – e.g. selection based on honesty and political/ideological compatibility with the voter.
Input 1: The Financial Hacker consists of the creation of a tool that allows civil society organizations to gather information on campaign costs made by political parties in the field. For example, if a political party organizes rallies, raffles, musical events, IDEA’s partners will estimate the costs for each activity. The information gathered will be sent to Oficina Nacional de Procesos Electorales (ONPE) for comparison against officially reported spending by each political party. The aim is that ONPE can use this information in its public reports that it periodically issues and to which the voting public can access. The official ONPE information will also be published on the web page.
Outputs: Information that will be available on the Web page, Perú decide bien [Peru decides well]; information that will be used and disseminated by the ONPE
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Input 2: Electoral Tool/Citizen’s Test is the primary messaging tool designed to promote issues that are of concern to citizens and promote candidate selection based on these issues.
Outputs: A tool that will be in the webpage Perú decide bien; an application for smart phones; a printed brochure for dissemination.
Input 3: The GPS Political Positions Locater facilitates comparisons between different political parties’ electoral platforms. This tool allows voters to analyze their preferences regarding to specific topics related to the administration of the city or the country and compares these to the platforms/ offerings of political parties.
Outputs: A virtual tool that will be in the webpage Perú decide bien, which does not yet exist; an application for smart phones; a character (the “Intruder”) that will participate in the public social mobilization events
Input 4: Social mobilization events are public events that will be held in heavily- transited locations (e.g. shopping mall where there is a high traffic of citizens; university campus). Entertaining activities will be held, the candidates will be introduced, and the Hacker character will be introduced. Additionally, there will also be stands with computers where citizens will be taught the tools and information spaces to learn more about their candidates and the parties up for election. It is also planned to distribute informational material (flyers) in these spaces. However, this depends on the amount of time available to distribute these materials.
Outputs: Media events; educated citizens; social network enhancement
IDEA will work throughout the Department of Ucayali, and will give “particular emphasis in the districts of Callería, Yarinacocha and Mananta districts due to their population density.
b. Outcomes The primary outcomes of interests are that 1) Citizens become equipped with the information and tools needed to better evaluate their candidates, and 2) Citizen awareness of the negative impact of illicit financing in electoral processes increases.
3. RESEARCH QUESTIONS AND POLICY There is a twofold problem at the core of the Lucha Program. First, voters tend to lack sufficient and accurate information about the role of illicit funds in Peruvian politics. Second, voters may remain indifferent toward corruption. As a result, voters may fail to negatively evaluate politicians with ties to illicit networks.
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Standard democratic theory predicts that when citizens know negative information about a candidate, they will be less likely to cast their vote for that candidate and this in turn deters politicians from engaging in illicit activities. The implication is that where elite corruption is rampant, it is because voters are either unaware of it, or that they fail to understand the negative consequences of corruption. Providing information to voters about which politicians engage in corruption, or sensitizing voters to the negative consequences of corruption more broadly, should help voters hold politicians to account for corruption and, in turn, deter elite corruption more generally. Similarly, the Lucha program proposes that mobilizing citizen awareness of corruption and its consequences will help reduce the influence of illegal interests on Peruvian political processes.
In practice, empirical evidence for this Theory of Change is mixed. After all, corrupt politicians are elected and reelected regularly (Golden 2006). Some studies have found that non-partisan information about incumbent corruption reduces their reelection chances substantially (Ferraz and Finan 2008; Pande 2011; see also Gottlieb 2012). Others have found that information about elite corruption has no effect on election outcomes, decreases turnout, or simply shifts corruption to other localities (Chong et al. 2011; de Figuereido et al. 2011; Olken 2007). Similarly, some studies that provided citizens with a broad scorecard about the performance of local incumbents (e.g., legislator spending, committee attendance, participation in the legislature) found that they increased voter knowledge and turnout, and sometimes affected election results (Banerjee et al. 2010; Bidwell et al. 2014). Others found that information about incumbent performance had minimal effects on voter choice (Humphreys and Weinstein 2012).
There may be several reasons for these disparate findings. One explanation relates to the idea that information matters differently to different sorts of people. For instance, different groups of voters may start from very different levels of knowledge about corruption or experience with corruption in politics. If true, awareness campaigns will not have uniform effects across publics. Another explanation is that contextual factors – such as national economy or incumbent performance – may affect whether voters are indifferent to corruption even when they are aware that it exists. Zechmeister and Zizumbo-Columba (2013) report that corruption voting in 19 Latin American countries is more pronounced when economic conditions or perceptions of the national economy are poor. Others find varying results with respect to whether voters are willing to overlook corruption when politicians otherwise perform well in office, delivering public goods to their constituents (Barbera et al. 2013; Muñoz et al. 2013; Winters and Weitz- Shapiro 2013). A more simple explanation is that interventions and outcome measures vary dramatically within sets of studies. There is thus room for new studies to make a significant contribution by varying the mode of delivering information and of measuring outcomes.
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The Lucha Program affords the opportunity to reexamine the assumed linkages between citizen information about corruption and democratic hygiene. Moreover, it provides a setting in which to investigate the political consequences of corruption at the more local level, where corruption may be more visible, but also potentially less costly. Thus, there are several basic research questions at the core of this impact evaluation:
■ Does increasing the accuracy and availability of information about corrupt party/campaign practices lead to increased voter knowledge of, interest in, and preferences against illicit interests in Peruvian political processes? ■ What type of information (“message content”) and mode of delivery (“message platform”) – generate the most interest in, and the strongest sensitization to, the problem? ■ Can social mobilization events generate broader networks of interest in and concern with political corruption in Peru? ■ To what extent do voters rely on this information to evaluate candidates? ■ To what degree do voters base their vote on this information relative to more traditional determinants of vote choice, like candidate issue positions or perceived ability to produce public goods? ■ Do voters scrutinize or punish candidates or parties in other ways – e.g. through casting “blank ballots” or by moving dishonest candidates down the list?
This impact evaluation will allow us to compare several varieties of messages about corruption and different modes of disseminating that information. As a result, this impact evaluation has the potential to adjudicate between disparate findings in the scholarly literature and also deliver concrete lessons to USAID/Peru and responsible government institutions, like ONPE and (Jurado Nacional de Elecciones) JNE, about how best to equip citizens to fight illicit interests in Peruvian politics.
4. OUTCOME INDICATORS OF INTEREST At the broadest level, this IE will address three outcomes of interest:
■ Awareness about corruption in politics; ■ Attitudes toward corruption in politics ■ Behavior with respect to support for parties with ties to corruption
Awareness ■ Knowledge of the key issues ■ Ability to identify candidates that have ties to illicit interests ■ Ability to identify potential consequences of corruption in politics
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Attitudes ■ Political efficacy ■ System legitimacy ■ Political and interpersonal trust ■ Social capital ■ Key determinants for evaluating candidates ■ Beliefs about most important political issues in Peru
Behaviors
Political information-seeking ■ Building on Laura Paler's and Victoria Shineman's work, we can conclude social mobilization events or face-to-face canvasing by distributing postcards with the IDEA-built website. We could track the unique code each person uses and trace it to a treatment vs. control area. ■ We could also trace their movement throughout the website provided that such technology is readymade and built in.
Non-voting political participation
■ Consider, for instance, pro-community activism, such as through signing petitions to resolve a community problem. ■ Engagement in clientelism, such as taking gifts from candidates.
Final vote choice
■ Might be best generated with a survey experiment for electoral support.
Such outcomes will be measured using a household survey, administered as a panel no later than one week prior to the election and again three weeks following the election. The questionnaire and specific measurement indicators are yet to be developed.
5. IDENTIFICATION STRATEGY This IE will use a household-based randomization strategy to best attribute outcomes of interest to the program. This decision is due to the relatively small geographic area where the program is occurring as well as the lack of geographically-located sub- constituency precincts, which limits our outcomes of interest to the individual level.
By using household randomization of information as an identification strategy, this impact evaluation can accurately measure outcomes given an environment where many
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political activities are occurring in a relatively small area. By assigning different treatment groups at the household level, the project increases the potential sample size to allow for the creation of a valid counterfactual control group through statistical sampling.
Broadly speaking, this IE will have two types of treatments. One is the presence of a social mobilization event (i.e. pre-election public fair) and the other is face-to-face messaging which forms the identification strategy. The household messaging will be of three types produced by IDEA:
■ Informational: e.g. basic facts about candidates’ funds declared v. funds spent ■ Normative: basic facts plus normative condemnation through the lens of democratic values/procedure ■ Consequentialist: basic facts plus sociotropic risks associated with corruption – e.g. health consequences of illegal mining; environmental effects of logging; violence and security.
To address the concern that the social mobilization events will attract citizens who are already more interested in politics, constituting a selection bias that threatens the inferences about impact, a randomized promotion strategy will be used to encourage a random subset of households to attend the event, using a face-to-face appeal. Those who attend the event will receive the whole combination of IDEA-generated information (types 1-3 above). Thus, this “randomized promotion” of IDEA’s social activities will serve as a proxy measure of true attendance at the social mobilization activity. The impact evaluation will, therefore, be able to test the assumption that “social activation activities will be of much utility… contributing to lodge the content and messages in the minds of citizens” (p. 24). A randomized promotion strategy will also increase the turnout to the social mobilization event, which is an additional benefit of this approach. This randomized promotion message will only be used in towns where there is a social mobilization event.
The other type of informational messaging will focus directly on the three types of information above to best understand which type is responsible for the greatest change in citizen knowledge, concern and behavior. Households will be randomly assigned to receive a purely informational message derived from IDEA’s investigative activities. Another group of households will receive this factual information with normative appeals created by the Electoral Tool. A final group of households will receive a message of the same factual information and a message that highlights the costs and consequences of illegal interests in politics. Sample messages are below:
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■ Informational (information drawn from Financial Hacker and Political GPS) ○ Facts and statistics about candidates for municipal election ■ Normative (messages about “good democracy,” based on the Electoral Tool) ○ Transparent campaigns are important to the function of democracy. ○ In a democracy, it is important to elect honest candidates. ○ In a democracy, honest candidates can best represent the interests of their constituents. ■ Consequential ○ Illegal industries, which are supported by corrupt candidates, hurt the health of your families and children through pollution of the environment and increased violent crime. ○ Illegal industries, which are supported by corrupt candidates, take away revenue from your communities that pays for health, education, water and sanitation.
These messages will be developed in conjunction with IDEA who can best articulate these appeals given their specialization in Peruvian politics.
It is not only possible to separate and identify the independent effects of different message content. It is also possible to analyze the relative effectiveness of delivering this information face-to-face through neighborhood canvassing vs. delivering this information through social mobilization activities.
While the different informational campaigns will be randomized at the household level, clearly the presence of a social mobilization event will not give financial and logistical constraints. The randomized promotion strategy for the mobilization events address this somewhat, by effectively increasing the salience of the event for certain households. However, through work with IDEA, the impact evaluation design can use a quasi- experimental matching strategy to assign one member of a pair of similar towns to receive the mobilization event or not. This will help address the urban bias of the events, where politics might differ considerably from more rural communities. If this cannot be accomplished, there will effectively be two similar, but non-comparable, impact evaluations in this design: in the presence of a mobilization event or not.
The table below outlines the different types of households. Given the experimental and randomized framework of this impact evaluation, before any activities take place the average baseline for household groups should be exactly the same for key indicators (excluding the presence of a mobilization event which is likely to be a non-random proxy for urbanization). After the interventions have been administered, the averages of different groups can be compared to measure the impact or effect of that specific
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intervention. Below also follows sample questions and comparisons that can be answered with this design.
Household Message Mobilization Event No Mobilization Event (Randomly Assigned) (Randomly Assigned) (Randomly Assigned) Control C1 C2 Informational Only T1 T4 Normative T2 T5 Consequential T3 T6
Example Questions and Comparisons:
■ What type of information – what “message content” – generates the most interest in, and sensitization to, the problem? ○ Which type of information matters most for citizens outcomes, either in the presence of a mobilization event or not? C1 v. T1 v. T2 v. T3; C2 v. T4 v. T5 v. T6 ■ What type of information delivery – what “message platform” – generates the most interest in, and sensitization to, the problem? ○ Do the social mobilization events promote knowledge and behavioral change in citizens? C1 v. T1 ○ Does the mode of engagement (community or face-to-face) affect citizen outcomes? T1 v. T4; T2 v. T5; T3 v. T6 (conditionally on attendance)
There are additional questions if we can better coordinate the location of the mobilization events to generate a quasi-experiment with a matching design to assign towns to receive a social mobilization event: ○ Does presence of a mobilization event affect outcomes without necessarily attending? T1 v. T4; T2 v. T5; T3 v. T6 ○ What is the size of the social networking spillover effect of the mobilization events? C1 v. C2
Finally, this IE can address the question of spillover effects and the saliency of social mobilization events in urbanized areas through the sampling strategy where enough households are brought into the experiment that are different distances from the site of the event, with distance serving as a proxy for the likelihood of attending an event given no outside encouragement to attend. This approach will once again require careful collaboration with IDEA as it selects the locations within towns for the mobilization events.
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6. SAMPLE To accurately calculate the number of people to be brought into this experimental design and to determine where they should be located within and between towns, the IE Team requires an accurate assessment of the population to say generalizable statements to larger Peruvian populations.
The IE-component of this project is taking place in the Ucayali Region of Peru. It is estimated that the impact evaluation will cover roughly 1000-2000 households between the different treatment and control groups. To figure out exactly how many and where these households will be, the impact evaluation and data collection teams will use a combination of the 2007 National Census including annual updates and the Instituto de Investigación Estadistico, Social y Económico’s panel survey that has representative demographic information at the regional level in Peru.
Within towns, sampling will be accomplished through a combination of city maps and random walking patterns by survey collectors to designate experimental households.
7. DATA COLLECTION Given the short timeframe for this impact evaluation, data collection activities need to be precisely timed. There will be a first round of data collection (“baseline”) approximately in Summer 2015 to help the messaging campaigns. This baseline data will be collected at the household-level in the pre-identified homes.
The private survey firm that will be hired, both to generate the appropriate sampling frame and collect the baseline survey, will also deliver the message treatments in the predetermined randomization strategy. This will consist of a small script variation as the survey closes as well as dropping off IDEA-produced materials that match the experimental treatment group the household is part of.
The second round of data collection (“midline”) will occur 4-5 weeks before the election in February and March 2016. This survey wave will be timed to the calendar of mobilization events being produced by IDEA.
The third round of data collection (“endline”) will occur approximately 2-3 weeks after the elections during the month of April. This data collection cannot be completed any later as memories of the election will become more unreliable past that point. The same households will be revisited and the same person within the household will be spoken to. This longer endline survey will include the same questions as the baseline and midline, but also a number of other political behavior and opinion questions as well as socio-economic information. This survey will be approximately 30-45 minutes long. The evaluation team co-PIs will analyze the data.
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8. TIMELINE As stated above, the timing of this impact evaluation is extremely tight given the elections calendar. Below is a timeline that combines targets for IDEA and data collection activities.
Spring 2015: IDEA finalizes the locations of the social mobilization events
Summer 2015: Baseline data collection
Fall 2015: IDEA and IE Team finalize language of different messaging campaigns and print campaign materials to precise specifications
Fall 2015: IDEA finalizes the specific activities at the social mobilization events to ensure consistency
February/March 2016: Midline, dissemination of messages, and social mobilization events held
April 10, 2016: Election Day
April 2016: Endline
Summer 2016: Data analysis by co-PIs and final impact evaluation report completed
9. RESEARCH TEAM Aaron Abbarno is a Democracy Fellow with the DCHA/DRG Learning Team. He is an expert in public opinion, surveys, and experimental designs in social science. He received his PhD from the University of Pittsburgh.
Nicole Bonoff is a Democracy Fellow with the DCHA/DRG Learning Team and post- doctoral lecturer at the University of Wisconsin, Madison. She is an expert in development issues, corruption and clientelism, and experimental designs in social sciences. She received her Ph.D. from the University of California, San Diego.
Noam Lupu is an assistant professor of political science at the University of Wisconsin, Madison. He is an expert on Latin American politics, political behavior, and experimental designs in social science. He received his PhD from Princeton University.
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ANNEX B, SURVEY INSTRUMENT
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OPINIONES POLITICAS EN LORETO Y UCAYALI, 2015-2016 OLA 1
D1: Región Loreto Ucayali 1 2
Filtro
F1. ¿Es usted ciudadano/a peruano/a? Sí 1 No 2 NS 88 NC 99
F2. ¿Cuántos años cumplidos tiene usted? NC 999
F3. Sexo de entrevistado (por observación) Masculino 1 Femenino 2
F4. Tipo de vivienda?: (por observación) Casa independiente 1 Departamento en edificio 2 Vivienda en quinta 3 Vivienda en casa de vecindad (callejón, solar o corralón) 4 Choza o cabaña 5 Vivienda improvisada 6 Local no destinado para habitación humana 7
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1. En su opinión ¿cuál es el problema más grave que está enfrentando el país? [NO LEER. OPCIÓN UNICA] Agua/ Electricidad (falta de) 1 Impunidad / falta de justicia 12 Corrupción de funcionarios públicos 2 Inflación / Altos precios 13 Corrupción de políticos 3 Los políticos /Mal gobierno 14 Delincuencia, crimen / Seguridad (falta de) 4 Medio ambiente 15 Derechos humanos, violaciones de 5 Pobreza 16 Desempleo/Falta de empleo 6 Protestas populares (huelgas, corte de calles, paros, etc.) 17 Desigualdad 7 Salud (falta o mala calidad del servicio) 18 Deuda externa 8 Transporte, problemas con el 19 Drogas, consumo de; drogadicción / Narcotráfico 9 Violencia 20 Economía (problemas con, crisis de) 10 Vivienda 21 Educación (falta de, mala calidad) 11 Otro 94 NS 88 NC 99
2. ¿Cuál es el segundo problema más grave que está enfrentando el país? [NO LEER. OPCIÓN UNICA] [DEBE SER DISTINTO A P1] NS 88 NC 99
3. ¿Cuál es el tercer problema más grave que está enfrentando el país? [NO LEER. OPCIÓN UNICA] ] [DEBE SER DISTINTO A P1 y P2] NS 88 NC 99
4. Hablando en general acerca del gobierno actual, ¿cómo calificaría la gestión del Presidente Ollanta Humala...?: [LEER OPCIONES] [MOSTRAR TARJETA] Muy buena 5 Buena 4 Ni buena, ni mala 3 Mala 2 Muy mala 1 NS 88 NC 99
RV1a: [PASAR A 6,7,8] RV1b: [SEGUIR A 5,6,7,8]
5. ¿Cree que la diferencia de ingresos entre ricos y pobres en el Perú de hoy es mucho mayor, mayor, igual, menor, o mucho menor que hace 20 años? [MOSTRAR TARJETA] Mucho mayor 5 Mayor 4 Igual 3 Menor 2 Mucho menor 1 NS 88 NC 99
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6. Ahora, hablando de la economía… ¿Cómo calificaría la situación económica del país? ¿Diría usted que es muy buena, buena, ni buena ni mala, mala o muy mala? [MOSTRAR TARJETA] Muy buena 5 Buena 4 Ni buena, ni mala 3 Mala 2 Muy mala 1 NS 88 NC 99
7. ¿Diría usted que durante los últimos 12 meses la situación económica de Perú ha mejorado mucho, ha mejorado, ha permanecido igual, ha empeorado, o ha empeorado mucho? [MOSTRAR TARJETA] Ha mejorado mucho 5 Ha mejorado 4 Ha permanecido igual 3 Ha empeorado 2 Ha empeorado mucho 1 NS 88 NC 99
8. ¿Cómo calificaría en general su situación económica personal? ¿Diría usted que es muy buena, buena, ni buena ni mala, mala o muy mala? [MOSTRAR TARJETA] Muy buena 5 Buena 4 Ni buena, ni mala 3 Mala 2 Muy mala 1 NS 88 NC 99 9. ¿Considera usted que su situación económica actual es mucho mejor, mejor, igual, peor, o mucho peor que la de hace 12 meses? [MOSTRAR TARJETA] Mucho mejor 5 Mejor 4 Igual 3 Peor 2 Mucho peor 1 NS 88 NC 99
10. En general, ¿cómo calificaría la gestión del alcalde de su municipio distrital? [LEER OPCIONES] Muy buena 5 Buena 4 Ni buena, ni mala 3 Mala 2 Muy mala 1 NS 88 NC 99
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11. En estas regiones, muchas personas trabajan en la tala de árboles y en la minería. ¿Cree usted que hay que reducir, aumentar, o mantener igual el número de puestos de trabajo en esas actividades? Reducir 1 Mantener igual 2 Aumentar 3 NS 88 NC 99
12. ¿Cree que la mayoría de los que trabajan en esas actividades lo hacen legalmente, o que la mayoría es ilegal? Mayoría legal 1 Mayoría ilegal 2 (NO LEER) Mitad y mitad 3 NS 88 NC 99
13. ¿Y cree que el gobierno debería hacer todo lo posible para limitar la tala ilegal y la minería ilegal? Sí 1 No 2 NS 88 NC 99
14. ¿Cree que el gobierno debería hacer todo lo posible para limitar el tráfico de drogas por estas regiones? Sí 1 No 2 NS 88 NC 99
15. ¿Y cree que el gobierno debería hacer todo lo posible para limitar la producción de coca ilegal por estas regiones? Sí 1 No 2 NS 88 NC 99
16. Si el gobierno tuviera que elegir entre proteger al medioambiente y promover el crecimiento económico, ¿cuál preferiría que elija? Proteger el medioambiente 1 Promover el crecimiento económico 2 NS 88 NC 99
17. Y si el gobierno tuviera que elegir entre proteger al medioambiente y combatir la corrupción en la política, ¿cuál preferiría que elija? Proteger el medioambiente 1 Combatir la corrupción 2
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NS 88 NC 99
18. Y si el gobierno tuviera que elegir entre combatir la corrupción en la política y promover el crecimiento económico, ¿cuál preferiría que elija? Combatir la corrupción 1 Promover el crecimiento económico 2 NS 88 NC 99
19. Si dependiera de usted, ¿qué haría para enfrentar el problema de la corrupción en la política? [LEER OPCIONES] Siempre enjuiciar y sancionar a los funcionarios corruptos, aun si ayudan a mejorar la economía y atienden las necesidades de la población 1 Enjuiciar y sancionar a los funcionarios corruptos solo si no ayudan a mejorar la economía y no atienden las necesidades de la población 2 Jamás enjuiciar a los funcionarios corruptos 3 NS 88 NC 99
20. Ahora le voy a leer una lista de grupos y organizaciones. Por favor, dígame si usted asiste a las reuniones de estas organizaciones: por lo menos una vez a la semana, una o dos veces al mes, una o dos veces al año, o nunca. Una vez Una o dos Una o dos Nunca NS NC a la veces al veces al semana mes año a. Reuniones de alguna organización 4 3 2 1 88 99 religiosa [ENC: (no misa] b. Reuniones de vecinos 4 3 2 1 88 99 c. Reuniones de una asociación de 4 3 2 1 88 99 profesionales d. Reuniones de un sindicato 4 3 2 1 88 99 e. Reuniones de un partido o 4 3 2 1 88 99 movimiento político f. Reuniones de un equipo de deportes 4 3 2 1 88 99 g. Reuniones de una asociación 4 3 2 1 88 99 agrícola
21. ¿Podría decirme si en los últimos 12 meses usted participó de alguna de las siguientes actividades? Sí No NS NC Bloqueo de calles, avenidas o caminos 1 2 88 99 Huelgas o paros 1 2 88 99 Marchas, manifestaciones o protestas públicas 1 2 88 99 Firma de una petición política 1 2 88 99
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22. En política la gente habla a menudo de “izquierda” y “derecha.” Usando una escala de 0 a 10, donde 0 significa IZQUIERDA y 10 DERECHA, ¿dónde se ubicaría usted? Izquierda Derecha NS NC 0 1 2 3 4 5 6 7 8 9 10 88 99
23. ¿Votó usted en las últimas elecciones presidenciales de 2011, en la primera vuelta? Sí 1 CONTINUAR CON P24 No 2 NS 88 PASAR A P26 NC 99
24. [SOLO COD 1 EN P23] ¿Se acuerda por quién votó en las últimas elecciones presidenciales de 2011, en la primera vuelta? [ESPONTÁNEA, NO LEER OPCIONES] Ninguno (fue a votar pero votó en blanco) 1 PASAR A 25 Ninguno (anuló su voto) 2 Ollanta Humala (Gana Perú) 3 Keiko Fujimori (Fuerza 2011) 4 Pedro Pablo Kuczynski (Alianza por el Gran Cambio) 5 PASAR A 27 Alejandro Toledo (Perú Posible) 6 Luis Castañeda Lossio (Solidaridad Nacional) 7 Otro: (especificar) 94 NS 88 PASAR A 27 NC 99 PASAR A 27
25. [SOLO A LOS QUE RESPONDIERON “NINGUNO (BLANCO O NULO)”, COD 1 o 2 EN P24] ¿Por qué votó usted nulo o blanco en las pasadas elecciones presidenciales, en la primera vuelta? [NO LEER OPCIONES; RESPUESTA UNICA] Estaba confundido, no sabía por quién votar, no conocía los candidatos 1 Quería demostrar su descontento con todos los candidatos, no le gustó ninguno 2 No creo en la democracia, quería protestar contra el sistema político 3 No creo en las elecciones o autoridades electorales 4 PASAR A 27 No me interesa la política 5 Mi voto no marca la diferencia 6 Otra razón: (especificar) 94 NS 88 PASAR A 27 NC 99 PASAR A 27
26. [SOLO PARA LOS QUE NO VOTARON EN LA PRIMERA VUELTA, SOLO COD 2 EN P23] ¿Por qué no votó en las pasadas elecciones presidenciales, en la primera vuelta? [Si dice “no voté porque no quería”, preguntar por qué no quiso votar] [NO LEER OPCIONES; RESPUESTA UNICA] Estaba confundido, no sabía por quién votar, no conocía los candidatos 1 No me gustaron los candidatos o la campaña 2 No creo en las elecciones o autoridades electorales 3 No creo en la democracia 4 Cuestiones burocráticas (registro, padrón) 5 Cuestiones de edad (muy joven, muy viejo) 6 No estaba en el distrito/estaba de viaje 7
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No me interesa la política 8 Otra razón 94 NS 88 NC 99
27. [PARA TODOS] ¿Y votó usted en las elecciones regionales y municipales en octubre de 2014? Sí 1 No 2 NS 88 NC 99
28. Independientemente de por cuál partido votó en la elección pasada o votará en la que viene, en general, ¿simpatiza usted con algún partido político en particular? Sí 1 PASAR A P30 No 2 CONTINUAR CON P29 NS 88 CONTINUAR CON P29 NC 99 CONTINUAR CON P29
29. [SOLO COD 2 EN P28] ¿Siente usted un poco más de simpatía por algún partido político que por los otros? Sí 1 CONTINUAR CON P30 No 2 PASAR A 32 NS 88 PASAR A 32 NC 99 PASAR A 32
30. [SOLO COD 1 EN P28 o COD 1 EN P29] ¿Con/por cuál partido? [ENC: NO LEER OPCIONES] [RPTA ÚNICA] [SI EL ENCUESTADO MENCIONA EL LÍDER DEL PARTIDO, MARCARLO COMO “OTROS” Y ESPECIFICAR EL NOMBRE] Acción Popular 1 Partido Popular Cristiano (PPC) 14 Alianza para el Progreso 2 Perú Más 15 Democracia Directa 3 Perú Posible 16 Esperanza Región Amazónica 4 Solidaridad Nacional 17 Fuerza Loretana 5 Somos Perú 18 Fuerza Popular 6 Tierra y Libertad 19 Mov. Amazónico Loreto 7 Todos Somos Ucayali 20 Mov. Cambio Ucayalino 8 Ucayali Región con futuro 21 Mov. Fuerza Ucayalina 9 Mov. Integración Loretana 10 Otros: especificar 94 Mov. Loreto - Mi Loreto 11 Partido Aprista Peruano- APRA 12 NS 88 Partido Nacionalista 13 NC 99
31. [SOLO COD 1 EN P28 o COD 1 EN P29] ¿Simpatiza con este partido mucho, algo o poco? Mucho 1 Algo 2 Poco 3 NS 88 NC 99
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32. [ PARA TODOS] ¿Qué tanto le interesa la política: mucho, algo, poco o nada? Mucho 4 Algo 3 Poco 2 Nada 1 NS 88 NC 99
33. Ahora voy a hacerle una serie de preguntas sobre su nivel de confianza en distintas instituciones. Considere una escala de 0 a 10, donde 0 significa que usted no tiene nada de confianza en la institución y 10 significa que usted tiene mucha confianza en esa institución. ¿Qué tanta confianza tiene usted en...? [MOSTRAR TARJETA] [PROGRAMADOR, ASIGNAR OPCIONES ALEATOREAMENTE] 0-10 NS NC a. El Poder Judicial 88 99 b. El Congreso Nacional 88 99 c. La policía nacional 88 99 d. Los partidos políticos 88 99 e. El Jurado Nacional de Elecciones (JNE) 88 99 f. La Oficina Nacional de Procesos Electorales (ONPE) 88 99 g. El Gobierno Regional 88 99 h. La Iglesia Católica 88 99 i. Los medios de comunicación 88 99 j. La Superintendencia Nacional de Aduanas y de 88 99 Administración Tributaria (SUNAT) k. La Defensoría del Pueblo 88 99 l. La Contraloría 88 99 m. Su municipalidad 88 99
34. Ahora le voy a leer una serie de afirmaciones y le voy a pedir que en cada caso me diga si usted está muy de acuerdo, algo de acuerdo, ni de acuerdo ni en desacuerdo, algo en desacuerdo o muy en desacuerdo? Ni de Muy de Algo de Algo en Muy en acuerdo ni NS NC acuerdo acuerdo desac. desac. en desac. a. Puede que la democracia 5 4 3 2 1 88 99 tenga problemas, pero es mejor que cualquier otra forma de gobierno b. El Estado debería tomar 5 4 3 2 1 88 99 medidas para reducir las diferencias en los niveles de ingreso de las personas c. El Estado, más que el sector 5 4 3 2 1 88 99 privado, debería ser el dueño de las empresas e industrias más importantes del país
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Ni de Muy de Algo de Algo en Muy en acuerdo ni NS NC acuerdo acuerdo desac. desac. en desac. d. El Estado, más que el sector 5 4 3 2 1 88 99 privado, debería ser el principal responsable de proveer los servicios públicos e. La gente como yo no tiene 5 4 3 2 1 88 99 ninguna influencia sobre lo que hace el gobierno f. A veces la política parece 5 4 3 2 1 88 99 tan complicada que la gente como yo no entiende mucho lo que pasa g. Hoy día, en el Perú hay 5 4 3 2 1 88 99 democracia h. Las elecciones regionales 5 4 3 2 1 88 99 del 2014 fueron limpias i. En Perú, todas las personas 5 4 3 2 1 88 99 son iguales ante la ley j. Los candidatos pueden 5 4 3 2 1 88 99 financiar sus campañas políticas con dinero obtenido de cualquier tipo de actividad k. Para el progreso del país, es 5 4 3 2 1 88 99 necesario que nuestros presidentes limiten la voz y el voto de los partidos de la oposición l. El pueblo debe gobernar 5 4 3 2 1 88 99 directamente y no a través de los representantes electos m. Aquellos que no están de 5 4 3 2 1 88 99 acuerdo con la mayoría representan una amenaza para el país
Cambiando un poco de tema…
[PROGRAMADOR: HAY DOS VERSIONES, ASIGNADAS ALEATORIAMENTE, DE LA SECUENCIA DE LAS PREGUNTAS 35-37:] RV2a: 35, 36, 37 RV2b: 36, 37, 35
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35. ¿Usted cree que el pedido de coimas y el abuso de cargos públicos para beneficio personal son hechos frecuentes en…? [LEER OPCIONES] Sí No NS NC a. Los empleados de la educación pública 1 2 88 99 b. Los empleados de la salud pública 1 2 88 99 c. Los empleados públicos a cargo de las contrataciones y 1 2 88 99 licitaciones públicas d. Los empleados públicos en general 1 2 88 99 e. Los políticos nacionales 1 2 88 99 f. Los políticos locales 1 2 88 99 g. La policía 1 2 88 99 h. Los jueces y fiscales 1 2 88 99
36. Durante los últimos 12 meses, ¿alguien le ha pedido a usted una coima? Sí 1 CONTINUAR CON P37 No 2 PASAR A 38 NS 88 PASAR A 38 NC 99 PASAR A 38
37. [SOLO COD 1 EN P36] ¿Quién? [ESPONTÁNEA, NO LEER OPCIONES; REGISTRAR TODAS LAS RESPUESTAS] Los empleados de la educación pública 1 Los empleados de la salud pública 2 Los empleados públicos a cargo de las contrataciones y licitaciones públicas 3 Los empleados públicos en general 4 Los políticos nacionales 5 Los políticos locales 6 La policía 7 Los jueces y fiscales 8 Otro (ESPECIFICAR) : ______94 No recuerda/ No sabe 88 No contesta 99
38. En términos generales, ¿Usted cree que el voto es secreto en Perú? Sí 1 No 2 NS 88 NC 99
39. Y pensando específicamente en alguien como usted que vota en un colegio de su localidad, ¿usted cree que los dirigentes políticos distritales, los partidos políticos, o el gobierno pueden saber cómo vota esa persona? Sí 1 No 2 NS 88 NC 99
40. Ahora le voy a mostrar una lista donde figuran varias actividades relacionadas con la política. Quisiera que me diga CUANTAS de estas situaciones fueron realizadas por usted este año. Por favor, no me diga cuáles ni cuantas veces, sino solamente
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CUANTAS de estas 4/5 situaciones realizó. [PROGRAMADOR ASIGNE EL NÚMERO SEGÚN LA LISTA DE ITEMS QUE SE MOSTRARÁN A CONTINUACIÓN].
[ENCUESTADOR: MOSTRAR TABLET Y ESPERAR QUE EL ENCUESTADO LEA LA LISTA]
[PROGRAMADOR: LOS ITEMS TIENEN QUE SER ROTADOS ALEATORIAMENTE Y LA LISTA DEBE ESTAR PREPARADA PARA SER MOSTRADA AL ENCUESTADO EN LA PANTALLA DE LA TABLET; EN CASO DE QUE EL ENCUESTADO NO SEPA LEER, ENCUESTADOR DEBE LEER LISTA DE ITEMS]
RV3a:
● Vio carteles de campaña en su barrio ● Habló de política con alguien ● Vio publicidad de campaña por TV y radio ● Fue candidato a algún cargo político
Una 1 Dos 2 Tres 3 Cuatro 4 Ninguna 96 NS 88 NC 99
RV3b:
● Vio carteles de campaña en su barrio ● Habló de política con alguien ● Vio publicidad de campaña por TV y radio ● Fue candidato a algún cargo político ● Recibió alguna ayuda material – como ropa o comida – o favor personal de algún candidato o referente político
Una 1 Dos 2 Tres 3 Cuatro 4 Cinco 5 Ninguna 96 NS 88 NC 99
41. Durante este año, ¿hubo vecinos en su barrio que recibieron alguna ayuda material – como ropa o comida – o favor personal de algún candidato o referente político? Sí 1 No 2 NS 88 NC 99
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42. Durante este año, ¿recibió usted alguna ayuda material – como ropa o comida – o favor personal de algún candidato o referente político? Sí 1 CONTINUAR CON P43 No 2 PASAR A 45 NS 88 PASAR A 45 NC 99 PASAR A 45
43. [SOLO COD 1 EN P42] ¿Usted conocía a este candidato o referente político? Sí 1 No 2 NS 88 NC 99
44. [SOLO COD 1 EN P42] ¿A qué partido pertenecía ese candidato o referente político? [NO LEER OPCIONES; SI EL ENCUESTADO MENCIONA EL LÍDER DEL PARTIDO, MARCARLO COMO “OTROS” Y ESPECIFICAR EL NOMBRE] [RPTA ÚNICA] Acción Popular 1 Partido Popular Cristiano (PPC) 14 Alianza para el Progreso 2 Perú Más 15 Democracia Directa 3 Perú Posible 16 Esperanza Región Amazónica 4 Solidaridad Nacional 17 Fuerza Loretana 5 Somos Perú 18 Fuerza Popular 6 Tierra y Libertad 19 Mov. Amazónico Loreto 7 Todos Somos Ucayali 20 Mov. Cambio Ucayalino 8 Ucayali Región con futuro 21 Mov. Fuerza Ucayalina 9 Mov. Integración Loretana 10 Otros: especificar 94 Mov. Loreto - Mi Loreto 11 Partido Aprista Peruano- APRA 12 NS 88 Partido Nacionalista 13 NC 99
45. [PARA TODOS] Ahora le voy a describir un escenario. Juan/a [PROGRAMAR SEGÚN SEXO DEL ENCUESTADO] vive en un barrio como el suyo en otra ciudad de Perú.
OPCIÓN 1 : [RV4a: El mes pasado, Juan/a tuvo que pagar un mes de sueldo al municipio para acelerar la aprobación de permisos para su empresa /
OPCIÓN 2: RV4b: El mes pasado, Juan/a recibió del municipio los permisos que necesitaba para su empresa sin tener que pagar coimas /
OPCIÓN 3: RV4c: Recientemente, Juan/a escuchó que varios funcionarios del municipio aceptaron coimas para otorgar contratos de concesiones públicas /
OPCIÓN 4: RV4d: Recientemente, Juan/a escuchó que el alcalde de la ciudad echó a varios funcionarios del municipio por aceptar coimas para otorgar contratos de concesiones públicas].
El alcalde de esa ciudad se presenta a reelección. Desde que fue elegido originalmente, las condiciones económicas de la ciudad y los servicios de salud y transporte han
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OPCIÓN 1: [RV5a: mejorado / OPCIÓN 2: RV5b: empeorado].
Teniendo en cuenta lo que le acabo de decir sobre el alcalde, ¿cuán probable le parece que Juan/a vote por él? [LEER OPCIONES] Nada probable 1 Poco probable 2 Algo probable 3 Muy probable 4 [NO LEER] No votaría por él / Votaría en blanco / Anularía el voto 96 NS 88 NC 99
46. ¿Y cuán probable es que el alcalde haya aceptado coimas? [LEER OPCIONES] Nada probable 1 Poco probable 2 Algo probable 3 Muy probable 4 NS 88 NC 99
47. Ahora le voy a leer una serie de afirmaciones sobre la corrupción en Perú. Le voy a pedir que en cada caso me diga si usted está muy de acuerdo, algo de acuerdo, ni de acuerdo ni en desacuerdo, algo en desacuerdo o muy en desacuerdo. [MOSTRAR TARJETA] Ni de Algo Muy de Algo de acuerdo Muy en en NS NC acuerdo acuerdo ni en desac. desac. desac. a. El gobierno debe hacer más para enfrentar el problema de la corrupción 5 4 3 2 1 88 99 en la política b. El gobierno debe hacer más para enfrentar el problema de la corrupción 5 4 3 2 1 88 99 entre los empleados públicos c. El gobierno debe hacer más para enfrentar el problema de la corrupción 5 4 3 2 1 88 99 en el sector privado d. Es necesario aceptar algo de corrupción para poder promover el 5 4 3 2 1 88 99 crecimiento de la economía e. La corrupción impacta mi salario 5 4 3 2 1 88 99 f. Si viera un acto de corrupción en mi 5 4 3 2 1 88 99 lugar de empleo, llamaría a la policía g. La corrupción establecida por Vladimiro Montesinos durante la presidencia de Alberto Fujimori se 5 4 3 2 1 88 99 justificó porque logró mejorar la economía
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Ni de Algo Muy de Algo de acuerdo Muy en en NS NC acuerdo acuerdo ni en desac. desac. desac. h. La corrupción establecida por Vladimiro Montesinos durante la presidencia de Alberto Fujimori se 5 4 3 2 1 88 99 justificó porque estaba luchando contra el terrorismo
48. ¿Sabe usted en qué año se promulgó la Constitución Política del Perú que sigue vigente hoy? [LEER OPCIONES] MOSTRAR TARJETA] En 1993 1 En 1979 2 En el 2001 3 NS 88 NC 99
49. ¿Y sabe cómo se llama el presidente de Brasil? [LEER OPCIONES] MOSTRAR TARJETA] Luiz Inácio Lula da Silva 1 Dilma Rousseff 2 Fernando Arias 3 NS 88 NC 99
50. ¿Sabe qué cargo político ocupa Alonso Segura Vasi? [LEER OPCIONES] MOSTRAR TARJETA] Ministro de Vivienda, Construcción y Saneamiento 1 Ministro de Defensa 2 Ministro de Economía y Finanzas 3 NS 88 NC 99
51. ¿Sabe cuántos congresistas tiene el Congreso? [LEER OPCIONES] [MOSTRAR TARJETA] Entre 25 y 100 1 Entre 101 y 175 2 Entre 176 y 250 3 NS 88 NC 99
52. ¿Y sabe usted si el gobernador de Loreto/Ucayali, Fernando Meléndez Celis/Manuel Gambini Rupay alguna vez fue investigado por temas de corrupción? Sí 1 No 2 NS 88 NC 99
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53. Ahora le quiero preguntar sobre cómo ve el mercado laboral. ¿Cuánto se imagina que gana al mes el gerente general de una empresa nacional grande en Perú? [EN SOLES] [REGISTRAR NÚMERO] NS 88 NC 99
54. ¿Cuánto se imagina que gana al mes un obrero en una fábrica? [EN SOLES] [REGISTRAR NÚMERO] NS 88 NC 99
55. ¿Y cuánto se imagina que gana al mes un albañil? [EN SOLES] [REGISTRAR NÚMERO] NS 88 NC 99
56. ¿Con qué frecuencia sigue usted información y noticias de las campañas electorales por…? (LEER MEDIO) [MOSTRAR TARJETA]: Varias Una vez a De vez Diario veces a la la en Nunca NS NC semana semana cuando a. Televisión 5 4 3 2 1 88 99 b. Radio 5 4 3 2 1 88 99 c. Periódicos 5 4 3 2 1 88 99 d. Internet 5 4 3 2 1 88 99 e. Redes sociales como Facebook y 88 99 5 4 3 2 1 Twitter
57. [SOLO PARA LOS QUE INDICARON EN EL FILTRO QUE UTILIZAN LA TELEVISIÓN, COD 5,4,3 o 2 EN P56a] ¿Cuál es el principal canal de televisión que mira para informarse sobre la situación del país? [MARCAR SOLO UNA] América TV 1 UTV19 12 Panamericana TV 2 Amazónica de Televisión 13 TV Perú 3 Loreto TV 14 ATV 4 Amazon Channel 15 Frecuencia Latina 5 Amazonia TV 16 Global TV 6 UCV Satelital 17 RPP TV 7 Selva TV 18 Canal N 8 Otro (especificar): 94 Canal Pucallpa 51 9 Canal Cultural visión 47 10 NS 88 Canal 33 La Ribereña 11 NC 99
58. [SOLO PARA LOS QUE INDICARON EN EL FILTRO QUE UTILIZAN LA RADIO COD 5,4,3 o 2 EN P56b] ¿Cuál es la principal radio que escucha para informarse sobre la situación del país? [MARCAR SOLO UNA]
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RPP 1 Radio Felicidad 11 Radio Pucallpa 2 La Zona 12 Radio Estar 3 Exitosa 13 Producciones Asturia 4 La Voz de la Selva 14 Estereo System 5 Radio La Karibeña 15 Radio Betel 6 Radio Nuevo Tiempo 16 Radio A 7 Lorecom 17 Radio Líder 8 Otra: ______94 Radio Video Oriente 9 NS 88 Radiodifusora Aroma 10 NC 99
59. [SOLO PARA LOS QUE INDICARON EN EL FILTRO QUE UTILIZAN UN DIARIO COD 5,4,3 o 2 EN P56c] Cuál es el principal diario que lee para informarse sobre la situación del país? [MARCAR SOLO UNA] El Comercio 1 Diario Pro & Contra 9 La República 2 Revista Selva Verde 10 El Trome 3 Revista Carta Abierta, revista de la Amazonía 11 Perú 21 4 Diario Crónicas 12 Correo 5 Diario A Hora 13 Ojo 6 Otro: ______94 Diario La Región 7 NS 88 Diario El Popular – Edición Loreto 8 NC 99
60. [SOLO PARA LOS QUE INDICARON EN EL FILTRO QUE UTILIZAN EL INTERNET COD 5,4,3 o 2 EN P56d] En el mes anterior, usted hizo uso del servicio de internet? Sí 1 No 2 NS 88 NC 99
61. [SOLO PARA LOS QUE INDICARON EN EL FILTRO QUE UTILIZAN EL INTERNET COD 5,4,3 o 2 EN P56d] En el mes anterior, usó usted el servicio de internet en: [LEER OPCIONES, RESPUESTA MÚLTIPLE] Su casa 1 La casa de un amigo/familiar 2 El trabajo 3 Un establecimiento educativo 4 Una cabina pública 5 Su teléfono celular 6 No utilicé el internet el mes anterior 7 Otro (especificar): 94 NS 88 NC 99
62. [SOLO PARA LOS QUE INDICARON EN EL FILTRO QUE UTILIZAN EL INTERNET COD 5,4,3 o 2 EN P56d] Usted usa internet al menos: [LEER OPCIONES] Una vez al día 1 Una vez a la semana 2 Una vez al mes 3 Cada 2 meses o mas 4 NS 88 NC 99
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63. [SOLO PARA LOS QUE INDICARON EN EL FILTRO QUE UTILIZAN EL INTERNET COD 5,4,3 o 2 EN P56d] Usted usa el internet para [LEER OPCIONES]: Sí No NS NC a. Obtener información 1 2 88 99 b. Comunicarse con amigos (email, chat, Facebook, Twitter) 1 2 88 99 c. Comprar productos y/o servicios 1 2 88 99 d. Operaciones de banca electrónica 1 2 88 99 e. Educación formal y actividades de capacitación 1 2 88 99 f. Transacciones con autoridades públicas 1 2 88 99 g. Actividades de entretenimiento (videos, YouTube, películas) 1 2 88 99
64. [PARA TODOS] ¿Se informa Ud. de los acontecimientos políticos del país…? [LEER OPCIONES] Sí No NS NC a. Por la familia 1 2 88 99 b. Por los amigos 1 2 88 99 c. Por los compañeros de trabajo o estudio 1 2 88 99 d. Por la iglesia 1 2 88 99 e. Por los maestros 1 2 88 99 f. Por el internet 1 2 88 99 g. Por los medios de comunicación 1 2 88 99 h. Otro: ______1 2 88 99
65. ¿Con qué frecuencia se informa usted sobre la actualidad política en el país? [LEER OPCIONES] [RESPUESTA ÚNICA] Frecuentemente 4 De vez en cuando 3 Sólo cuando le interesa algún tema 2 Nunca 1 NS 88 NC 99
66. Durante el año pasado, usted… [INSISTIR EN LA PREGUNTA AUN SI EL ENCUESTADO DICE QUE YA LAS RESPONDIÓ] Sí No NS NC a. ¿Habló de política con alguien? 1 2 88 99 b. ¿Vio carteles de campaña en su barrio? 1 2 88 99 c. ¿Vio publicidad de campaña por TV y radio? 1 2 88 99 d. ¿Fue candidato a algún cargo público? 1 2 88 99
67. ¿Cuál es el último año o grado de estudios que aprobó? [ESPONTÁNEA: NO LEER OPCIONES] Sin nivel 1 Educación inicial 2 Primaria incompleta 3 Primaria completa 4 Secundaria completa 5 Secundaria incompleta 6 Superior no universitaria incompleta 7
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Superior no universitaria completa 8 Superior universitaria incompleta 9 Superior universitaria completa 10 Postgrado completo o incompleto 11 NS 88 NC 99
68. ¿Cuántas personas en total viven en su hogar en este momento? [REGISTRAR NUMERO] NS 88 NC 99
69. ¿Cuántos de ellos son menores de 18 años? NS 88 NC 99
70. ¿Esta Ud. afiliado a algún sindicato? Sí 1 No 2 NS 88 NC 99
71. ¿Algún otro miembro de su familia está afiliado a algún sindicato? Sí 1 No 2 NS 88 NC 99
72. ¿A qué se dedica usted principalmente? ¿Está usted actualmente…? [LEER OPCIONES] Trabajando (a tiempo completo o parcial) 1 CONTINUAR CON P73 Está buscando trabajo activamente 2 PASAR A 75 Está jubilado, pensionado o incapacitado permanentemente para trabajar 3 PASAR A 75 Es estudiante 4 PASAR A 76 Se dedica a los quehaceres de su hogar 5 PASAR A 76 No trabaja y no está buscando trabajo 6 PASAR A 76 NS 88 PASAR A 76 NC 99 PASAR A 76
73. [SOLO COD 1 EN P72] ¿Cuál es su principal ocupación? [COSAS COMO OBRERO INDUSTRIAL, MAESTRO, COLECTIVERO, MÉDICO, ABOGADO, EMPLEADA DOMÉSTICA, ETC.] Agricultor 1 Otro (especificar) 94 NS 88 NC 99
74. [SOLO PARA LOS QUE INDICARON QUE TRABAJAN COMO AGRICULTOR EN P73, COD 1 EN P73] [RPTA UNICA] ¿Qué producto cultiva principalmente? Café 1 Frutas (naranjas, papaya,etc) 7 Cacao 2 Soya 8 Plátano 3 Otro (especificar) 94
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Arroz 4 Maíz 5 NS 88 Yuca 6 NC 99
75. [SOLO COD 2 o 3 EN P72] ¿Cuál fue su principal ocupación? [COSAS COMO OBRERO INDUSTRIAL, MAESTRO, COLECTIVERO, MÉDICO, ABOGADO, EMPLEADA DOMÉSTICA, ETC. NS 88 NC 99
76. [PARA TODOS] ¿En cuál de los siguientes rangos se encuentran los ingresos familiares mensuales de este hogar, incluyendo las remesas del exterior y el ingreso de todos los adultos e hijos que trabajan? [SI NO ENTIENDE, PREGUNTE: ¿Cuánto dinero entra en total a su casa al mes?] S/.260 o menos 1 S/. 1261 a S/. 1560 7 S/. 261 a S/. 460 2 S/. 1561 a S/. 2060 8 S/. 461 a S/. 660 3 S/. 2061 a S/. 3060 9 S/. 661 a S/. 860 4 Más de S/. 3060 10 S/. 861 a S/. 1060 5 NS 88 S/. 1061 a S/. 1260 6 NC 99
77. Imagínese una escalera con 10 escalones. En el 1 se ubican los peruanos más pobres y en el 10 se ubican los peruanos más ricos. ¿Dónde se ubicaría usted? [NO LEER OPCIONES] 1 1 2 2 3 3 4 4 5 5 6 6 7 7 8 8 9 9 10 10 NS 88 NC 99
78. ¿Cuál es su estado civil? [LEER OPCIONES] Soltero 1 Casado 2 Unión libre (conviviente) 3 Divorciado 4 Separado 5 Viudo 6 NS 88 NC 99
79. ¿Usted se considera una persona Asháninka, Aymara, blanca, Bora, mestiza, negra, oriental, Quechua, Shipibo, u otra? Asháninka 1 Oriental 7 Aymara 2 Quechua 8
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Blanca 3 Shipibo 9 Bora 4 Otra (ESPECIFICAR) 94 Mestiza 5 NS 88 Negra 6 NC 99
80. Si usted es de alguna religión, ¿podría decirme cuál es su religión? [NO LEER OPCIONES] Católica 1 Religiones Tradicionales 7 Protestante 2 Judío 8 Religiones Orientales no Cristianas 3 Agnóstico o ateo 9 Ninguna 4 Testigos de Jehová 10 Evangélica, Pentecostal y Adventista 5 NS 88 Mormón 6 NC 99
81. ¿Cuál es el idioma o lengua maternal que aprendió en su niñez? [NO LEER OPCIONES] Asháninka 1 Portugués 6 Aymara 2 Shipibo 7 Bora 3 Otra: 94 Castellano/Español 4 NS 88 Inglés 5 NC 99
82. Para finalizar, ¿Podría decirme cuáles de los siguientes objetos tienen en el hogar? Tiene No tiene NS NC a. Refrigeradora 1 2 88 99 b. Teléfono fijo (no celular) 1 2 88 99 c. Teléfono celular 1 2 88 99 d. Carro 1 2 88 99 e. Lavadora de ropa 1 2 88 99 f. Microondas 1 2 88 99 g. Moto 1 2 88 99 h. Agua potable dentro de la vivienda 1 2 88 99 i. Cuarto de baño dentro de la casa 1 2 88 99 j. Computadora 1 2 88 99 k. Servicio de Internet 1 2 88 99 l. Televisión 1 2 88 99 m. Televisor de pantalla plana 1 2 88 99
FIN DE LA ENTREVISTA
PREGUNTAS PARA EL ENCUESTADOR [ENCUESTADOR, NO FORMULE ESTAS PREGUNTAS, ESTAS DEBEN SER RESPONDIDAS POR USTED]:
83. ¿Cómo calificaría el nivel de conocimiento del encuestado sobre política en general? Muy bajo 1 Bajo 2 Ni bajo ni alto 3 Alto 4 Muy alto 5 NS 88 NC 99
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84. Finalmente, también nos gustaría saber si había otro adulto presente durante la entrevista. Sí 1 No 2 NS 88 NC 99
D2: Provincia
LORETO UCAYALI Alto Coronel Padre Loreto Maynas Requena Ucayali Amazonas Portillo Abad 1 2 3 4 5 6 7
D3: Distrito Distrito
D4: Centro poblado Centro Poblado
CLASIFICACIÓN DE NSE (PREGUNTAR POR EL JEFE DEL HOGAR) – ENTREVISTA CARA A CARA
(LEER) Con la finalidad de agrupar sus respuestas con las de otras personas similares a usted, nos gustaría que responda las siguientes preguntas referidas al jefe de hogar: EL JEFE DE HOGAR es aquella persona, hombre o mujer, de 15 años o más, que vive en la casa y que aporta más dinero o toma las decisiones financieras de la familia. EL HOGAR es el conjunto de personas que, habitan en la misma vivienda y preparan o consumen sus alimentos en común. N1. ¿Cuál es el máximo nivel de instrucción alcanzado por el jefe del hogar? (ACLARAR “COMPLETA O INCOMPLETA”) Sin educación/ Educación Inicial 0 Superior Técnico 3 Superior Univ. Completa 5 Completa Primaria incompleta o completa/ 1 Superior Univ. 4 Post-Grado Universitario 7 Secundaria incompleta Incompleta Secundaria completa/ Superior 2 Técnico Incompleta
N2. ¿Cuál de estos bienes tiene en su hogar que esté funcionando? (LEER CADA ARTÍCULO Y REGISTRAR) NO SI Computadora, laptop, tablet en funcionamiento 0 2 Lavadora en funcionamiento 0 2 Horno microondas en funcionamiento 0 2
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NO SI Refrigeradora/ Congeladora en funcionamiento 0 2 SUMAR PUNTAJE
N3.a. El jefe de su hogar ¿tiene algún auto o camioneta? (SI NO TIENE REGISTRAR 0, SI TIENE CONTINUAR) Y, ¿el auto es de su propiedad o de una empresa?, ¿lo usa para taxi o no? (SI ES DE SU PROPIEDAD Y LO USA PARA TAXI REGISTRAR CÓDIGO 0; DE LO CONTRARIO REGISTRAR 5) NO SI a. Auto o camioneta solo para uso particular (NO TAXI NI AUTO DE 0 5 LA EMPRESA)
N3.b. En su hogar, ¿tiene servicio doméstico, es decir, una persona que ayuda con las tareas del hogar y a la que se le paga? (SI NO TIENE REGISTRAR CÓDIGO 0; SI TIENE CONTINUAR) ¿Y cuántas veces por semana viene a trabajar? (SI VIENE A TRABAJAR 1 O MÁS VECES POR SEMANA REGISTRAR CÓDIGO 5, DE LO CONTRARIO REGISTRAR 0) NO SI b. Servicio doméstico en el hogar pagado (MINIMO QUE VAYA AL 0 5 HOGAR UNA VEZ POR SEMANA)
N4. En esta tarjeta aparecen materiales que se usan en los pisos de las viviendas. ¿Cuál es el material predominante en los pisos de su vivienda? (MOSTRAR TARJETA) (CONSIDERAR EL PISO DENTRO DEL ÁREA CONSTRUIDA.RESPUESTA ÚNICA) Tierra / Otro material (arena y tablones sin 0 Laminado tipo madera, láminas 7 pulir) asfálticas o similares Cemento sin pulir o pulido / Madera 3 Parquet o madera pulida y similares; 8 (entablados)/ tapizón porcelanato, alfombra, mármol Losetas / terrazos, mayólicas, cerámicos, 5 vinílicos, mosaico o similares
N5. El jefe de su hogar ¿está afiliado a algún sistema de prestaciones de salud que aparece en esta tarjeta? (MOSTRAR TARJETA) (REGISTRE TODOS LOS QUE TIENE Y PARA CALCULAR EL NSE CONSIDERE EL MAYOR PUNTAJE). Código Puntaje Código Puntaje No está afiliado a ningún Seguro Salud FFAA/ 1 0 4 4 seguro Policiales Seguro Integral de Salud Entidad prestadora de salud 2 5 6 (SIS) (EPS) ESSALUD 3 2 Seguro privado de salud 6
N6. En esta tarjeta aparecen materiales que se usan para construir paredes. ¿Cuál es el material predominante en las paredes exteriores de su vivienda? (MOSTRAR TARJETA) (SE REFIERE AL MATERIAL DE LA PARED Y NO AL REVESTIMIENTO. RESPUESTA ÚNICA) Estera 0 Piedra, sillar con cal, cemento 4
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Madera, Piedra con barro, Quincha (caña con barro), Tapia, Adobe 2 Ladrillo o bloque de cemento 6
N7. ¿Tiene baño en su hogar o no? (SI NO TIENE REGISTRAR CÓDIGO 0, SI TIENE CONTINUAR) ¿Está el baño conectado al sistema de desagüé o está conectado a un pozo, silo, río, acequia o canal? (SI ESTÁ CONECTADO AL DESAGUE CONTINUAR, DE LO CONTRARIO REGISTRAR CÓDIGO 1) ¿Y el baño es compartido fuera de la vivienda o está dentro de su vivienda? NO TIENE O NO ESTÁ CONECTADO A UN SÍ ESTÁ CONECTADO AL DESAGUE DESAGUE (SIN RED PÚBLICA) (CON RED PÚBLICA) No tiene baño 0 Baño compartido fuera de la vivienda. 3 Baño que da a un pozo ciego, pozo séptico, silo, 1 Baño dentro de la vivienda 5 río, acequia o canal dentro o fuera del hogar N1 + .12 puntos o .De 29 a 33 NSE E 8 NSE B2 4 menos puntos N2 .De 13 a 19 .De 34 a 39 NSE D 7 NSE B1 3 puntos puntos
N3.a .De 20 a 22 NSE .De 40 a 47 6 NSE A2 2 puntos C2 puntos N3.b .De 23 a 28 NSE . 48 puntos a 5 NSE A1 1 puntos C1 más N4 N5 puntaje N6 N7 Total
DATOS DEL ENTREVISTADO
N8. MAIL. ¿Tiene usted correo electrónico? ¿Cuál es el correo electrónico que utiliza con mayor frecuencia? Hotmail. 1 Hotmail.es 4 com CORR Yahoo.c @ 2 Yahoo.es 5 EO om Gmail.c Otro 3 94 om (especificar)
N11. AÑO N10. EDAD. N9. ANIONAC. Masculino 1 Femenino 2 ¿Cuál es su GENERO. Año de edad exacta? Nacimiento
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Le recuerdo que esta encuesta es anónima; sin embargo, quisiera por favor que me proporcione los siguientes datos para que el supervisor verifique la correcta realización de mi trabajo...
NOMBRES APELLIDOS
TELÉFONO. FIJO CELULAR CÓDIGO NÚMERO NÚMERO 1 1 2 NÚMERO 2 1 2
Dirección: ______
DISTRITO. Provincia / ZONA. MANZANA. Distrito (UBIGEO): Zona: Manzana:
CODENC. Código Encuestador:
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ANNEX C, SURVEYED LOCALITIES The table below provides a list of the 40 localities surveyed in the regions of Loreto and Ucayali as part of this baseline study.
Surveyed localities in the regions of Loreto and Ucayali
Province District Districts capitals (Urban) Area Towns / Villages (Rural) LORETO Maynas Belen Belen Urban Maynas Iquitos Iquitos Urban Maynas Punchana Punchana Urban Maynas San Juan Bautista San Juan Bautista Urban Requena Requena Requena Urban Alto Amazonas Yurimaguas Yurimaguas Urban Maynas Indiana Indiana Urban Maynas Mazan Mazan Urban Loreto Nauta Nauta Urban Ucayali Vargas Guerra Orellana Urban Maynas Fernando Lores Tamshiyacu Rural Alto Amazonas Lagunas Lagunas Rural Requena Jenaro Herrera Jenaro Herrera Rural Maynas San Juan Bautista Santa Clara Rural Mariscal Ramon Castilla San Pablo San Pablo Rural Maynas San Juan Bautista Santo Tomas Rural Maynas Belen San Jose Rural Loreto San Juan Bautista 13 de Febrero Rural Maynas Iquitos Manacamiri Rural Maynas Punchana Barrio Florida Rural UCAYALI Coronel Portillo Calleria Calleria Urban Coronel Portillo Yarinacocha Yarinacocha Urban Coronel Portillo Manantay Manantay Urban Padre Abad Padre Abad Aguaytia Urban Coronel Portillo Campoverde Campoverde Urban Padre Abad Irazola San Alejandro Urban Coronel Portillo Nueva Requena Nueva Requena Urban Coronel Portillo Iparia Iparia Urban Padre Abad Irazola Alexander von Humboldt Rural Padre Abad Irazola Monte Alegre Rural Coronel Portillo Yarinacocha San Jose Rural Padre Abad Padre Abad Boqueron Rural
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Province District Districts capitals (Urban) Area Towns / Villages (Rural) Padre Abad Irazola Nuevo Tahuantinsuyo Rural Padre Abad Padre Abad Previsto Rural Coronel Portillo Yarinacocha Nueva Esperanza de Panaillo Rural Coronel Portillo Campoverde San Jose Rural Coronel Portillo Campoverde La Merced de Neshuya Rural Coronel Portillo Yarinacocha San Juan Rural Padre Abad Padre Abad Santa Rosa Rural Coronel Portillo Yarinacocha San Lorenzo Rural
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ANNEX D, BALANCE REPORT To ensure randomization was conducted successfully, the IE team tested for differences in key household characteristics across the treatment and control groups. Although the team found some imbalances across groups, the randomization, overall, appears to have been successful. Educational attainment is higher in the treatment group, but the difference, while statistically significant, is so small that it is not significant in practical terms. The difference in household income is the most striking as it suggests the treatment group is slightly better off than the control group. However, this may be partially attributable to the imprecision of the income ranges. The IE team also tested for differences in 13 household assets. Of these, ownership rates are similar across the groups for 11 of the 13 assets. However, refrigerators and potable water are found at slightly higher rates within the treatment group. To further assess balance, the IE team tested for differences across the treatment and control groups using 2007 census data aggregated at the locality level. In particular, the team tested 9 measures of population and socioeconomic status: total population; urban population; rural population; total households; urbanity; education rate; employment rate; literacy rate; and primary language spoken. The team found no statistically significant differences across treatment status for any of these variables, which again suggests the randomization procedure was successful. Balance tests for key demographic variables Significance Variable N Control Treatment (p-value) 37.90 37.31 Age 1000 0.487 (.61) (.59) 0.492 0.498 Sex 1000 0.850 (.022) (.022) 5.36 5.60 Education 1000 0.051 (.09) (.08) 5.17 5.35 Household size 1000 0.432 (.11) (.20) 3.84 4.18 Household income 880 0.033 (.114) (.111) 0.546 0.593 Employed 999 0.132 (.022) (.022) 1.17 1.24 Political knowledge 1000 0.289 (.047) (.049) 0.384 0.436 Refrigerator 1000 0.095 (.021) (.022) 0.128 0.122 Telephone (landline) 1000 0.775 (.015) (.015)
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Significance Variable N Control Treatment (p-value) 0.667 0.692 Telephone (cellular) 999 0.404 (.021) (.021) 0.020 0.014 Automobile 1000 0.464 (.006) (.005) 0.112 0.104 Washing machine 1000 0.684 (0.14) (.014) 0.720 0.066 Microwave 1000 0.701 (.012) (.011) 0.306 0.304 Motorcycle 1000 0.945 (.021) (.021) 0.454 0.538 Potable water 1000 0.001 (.022) (.022) 0.278 0.234 Home bathroom 999 0.115 (.020) (.019) 0.112 0.128 Computer 1000 0.437 (.014) (.015) 0.066 0.066 Internet 1000 1.000 (.011) (.011) 0.758 0.772 Television 1000 0.602 (.019) (.019) 0.230 0.232 Flat-screen television 1000 0.940 (.019) (.019)
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