Supplementary material for

State Coercion and Control Aversion: Evidence from an Internet Study in East and West Germany

Katrin Schmelz and Anthony Ziegelmeyer

This version: February 2020

Appendix A contains the screens of the instructions, belief elicitations and decisions (English transla- tions). Appendix B provides additional details about our sample. Appendix C contains data analyses which complement the analysis of our main experiment in the paper. Finally, Appendix D presents our robustness experiment with students.

Contents

A Experimental screens 2

B Main experiment: Sample details on jobs, dropouts and migrants 13 B.1 Eliciting job characteristics ...... 13 B.2 Reasons for dropouts ...... 13 B.3 Details about migrants ...... 14

C Main experiment: Complementary data analysis 15 C.1 Cumulative frequencies of agents’ effort ...... 15 C.2 Agents’ effort over time ...... 16 C.3 Agents’ intrinsic motivation over time ...... 16 C.4 Agents’ effort differences ...... 17 C.5 Agents’ control aversion in East and West over time ...... 21 C.6 Perceived and desired control and freedom at work ...... 22 C.7 Robustness of hypotheses 1 and 2: Effort costs of control aversion ...... 23 C.8 Robustness of hypothesis 2: Varying the age cutoff ...... 26 C.9 Older German migrants ...... 27 C.10 Dynamics of the reactions to control and agents’ types ...... 29 C.11 Strength of agents’ control aversion ...... 37 C.12 Agents’ beliefs ...... 39 C.13 Principals’ control decisions ...... 41 C.14 Principals’ beliefs ...... 44 C.15 Principals’ best replies ...... 46

D Robustness experiment with students 48 D.1 Locations of the robustness experiment ...... 48 D.2 Design and procedures ...... 49 D.3 Students’ behavior in East and West Germany ...... 51 D.4 Students’ behavior in the methodological treatments ...... 54

1 A Experimental screens

Below we provide the main screens of the experiment. The instructions were identical for principals and agents.

2 The experiment: instructions

In this experiment, you will make decisions for which you will receive points. Remember, the exchange rate from points to euros is as follows:

1 point = 0.15 euros

General procedure One half of the participants will be named A and the other half of the participants will be named B. The experiment consists of 10 rounds. You will learn whether you are participant A or B before the beginning of the first round. You will keep your name over all rounds. In every round, for all participants, one participant A and one participant B will be matched randomly. The participant you are matched with in a given round will never be matched with you in any later round. No participant will learn with whom he has interacted. Every round follows the same procedure. Participants make decisions in the following situation: Imagine an arrange- ment where participant B completes a task for participant A. Participant B decides on a symbolic effort level (at least 1 and at most 10) to complete the task. The effort of B is beneficial for A and costly for B. Accordingly, the higher the effort level of B, the higher the income of A and the lower the income of B. Participant A decides whether to force participant B to exert a minimum effort level of 1, 2, or 3. Before decisions are made in a given round, all participants guess what other participants will decide in that round.

On the next pages, you will learn in more detail about the decisions, the guesses, and the incomes.

Page Next, we explain the decisions. B 1 Next

1 The experiment: instructions

The decisions Both participants make their decisions at the same time. Therefore, each participant makes his decision without knowing what the other participant decides.

Participant A decides on one of the following three options: Option 1: A forces B to exert an effort level of at least 1. Option 2: A forces B to exert an effort level of at least 2. Option 3: A forces B to exert an effort level of at least 3.

Participant B decides on an effort level for each of the following three cases: Case 1: A chooses option 1. Thus, B can choose any effort level between 1 and 10. Case 2: A chooses option 2. Thus, B can choose any effort level between 2 and 10. Case 3: A chooses option 3. Thus, B can choose any effort level between 3 and 10.

Consequently, participant A makes one decision and participant B makes three decisions. The option chosen by A determines the case in which the effort level chosen by B is relevant for calculating the incomes of both participants. The following table shows the incomes of both participants depending on the effort level of B.

Effort level of B 12345678910 Income of A (in points) 1 162941536475828790 Income of B (in points) 99 98 96 93 89 83 75 65 51 35

Page Next, we explain the guesses and the incomes. C B Previous 1 2 Next

2 The experiment: instructions

The guesses Participant A guesses the effort level all participants B will choose on average in case 1, in case 2, and in case 3. Participant B guesses how many participants A will decide on option 1, on option 2, and on option 3. Thus, each participant makes three guesses per round. The guesses always refer to the current round. If your guess is close to the actual value then you will receive 70 points. Otherwise you will receive 20 points.

End of the rounds At the end of each round, you will learn the decision of the participant you were matched with in that round. You will also learn what your incomes resulting from your decisions are. Only after the experiment is over will you find out whether your guesses were right.

Summary and calculation of the payment The experiment consists of 10 rounds. In every round, for all participants, one participant A and one participant B will be matched. A decides on the minimum effort level he enforces from B. B decides on an effort level for each potential decision of A. Before the decisions are made, each participant guesses what the other participants will decide. After the experiment is over, one round will be selected at random for payment. Each round has the same probability to be selected. Whether the payment is calculated based on the decisions or on the guesses of that round will again be selected at random and with equal probability. Only one of the three guesses will be selected and each guess is given the same probability.

Page Click “Next” when you have finished reading the instructions. C B Previous 12 3 Next

3 The experiment: control questions INSTRUCTIONS

To answer the control questions please see the respective incomes in the table.

Effort level of B 12345678910 Income of A (in points) 1 162941536475828790 Income of B (in points) 99 98 96 93 89 83 75 65 51 35

Question 1: Suppose participant A forces B to exert What are the incomes? an effort level of at least 1. In this case, participant B chooses an Income of A: 1q points effort level of 1. Income of B: 1q points

Question 2: Suppose participant A forces B to exert What are the incomes? an effort level of at least 2. In this case, participant B chooses an Income of A: 1q points effort level of 7. Income of B: 1q points

Question 3: Suppose participant A forces B to exert What are the incomes? an effort level of at least 3. In this case, participant B chooses an Income of A: 1q points effort level of 4. Income of B: 1q points

Please answer the questions.

1 The experiment: you are ...

You are participant A.

In each round, you will be matched with a different participant B.

Round 1 is about to start. 15s

1 The experiment: make a guess! INSTRUCTIONS

What do you guess is the average effort level of all participants B in case 1, in case 2, and in case 3 in this round? If your guess does not differ by more than 0.5 from the actual average effort level for a given case then you will receive 70 points. Otherwise you will receive 20 points. No other participant will ever know your answer. Please always insert an integer without decimals.

I guess the average effort level of all participants B is ...

Case 1: about15 when they are forced to exert an effort level of at least 1.

Case 2: about15 when they are forced to exert an effort level of at least 2.

Case 3: about15 when they are forced to exert an effort level of at least 3.

The general income table is shown Effort level of B 1 2 3 4 5 6 7 8 910 once more for visualization: Your income (in points) 1 16 29 41 53 64 75 82 87 90 Income of B (in points) 99 98 96 93 89 83 75 65 51 35

Please answer the questions.

2 The experiment: decide! INSTRUCTIONS

You can force participant B to exert a minimum effort level of 1, 2, or 3. At the same time, participant B chooses an effort level from each of the following three tables. Your decision determines which of the three decisions of B will be relevant for calculating the incomes. Please choose one of the following three options.

Which minimum effort level do you enforce from participant B?

Option 1: I force B to exert an effort level of at least 1. hw Effort level of B 1 2 3 4 5 6 7 8 910 Your income (in points) 1 16 29 41 53 64 75 82 87 90 Income of B (in points) 99 98 96 93 89 83 75 65 51 35

Option 2: I force B to exert an effort level of at least 2. hw Effort level of B 1 2 3 4 5 6 7 8 910 Your income (in points) 16 29 41 53 64 75 82 87 90 Income of B (in points) 98 96 93 89 83 75 65 51 35

Option 3: I force B to exert an effort level of at least 3. hw Effort level of B 1 2 3 4 5 6 7 8 910 Your income (in points) 29 41 53 64 75 82 87 90 Income of B (in points) 96 93 89 83 75 65 51 35

Please answer the question.

4 The experiment: you are ...

You are participant B.

In each round, you will be matched with a different participant A.

Round 1 is about to start. 15s

1 The experiment: make a guess! INSTRUCTIONS

Assume there are 100 participants A (the actual number of participants A will be converted to 100). What do you guess, how many participants A will decide on the options 1, 2, and 3 in this round? If your guess does not differ by more than 5 from the converted number of participants A who actually decide on a given option then you will receive 70 points. Otherwise you will receive 20 points. No other participant will ever know your answer. Please always insert an integer without decimals. Note that the three numbers have to sum up to 100.

I guess out of 100 participants A, ...

Option 1: about 15 force their participant B to exert an effort level of at least 1.

Option 2: about 15 force their participant B to exert an effort level of at least 2.

Option 3: about 15 force their participant B to exert an effort level of at least 3.

The general income table is shown Your effort level 1 2 3 4 5 6 7 8 910 once more for visualization: Income of A (in points) 1 16 29 41 53 64 75 82 87 90 Your income (in points) 99 98 96 93 89 83 75 65 51 35

Please answer the questions.

2 The experiment: decide! INSTRUCTIONS

Participant A decides whether to force you to exert an effort level of at least 1, 2, or 3 (without knowing what you decide). Since you do not yet know the decision of A you have to choose an effort level for each of the three cases. The decision of A determines which of your three decisions will be relevant for calculating the incomes. In each table, click on the column of the effort level you want to choose.

Which effort level do you choose?

Case 1: Assume that A forces you to exert an effort level of at least 1.

Your effort level 1 2 3 4 5 6 7 8 910 Income of A (in points) 1 16 29 41 53 64 75 82 87 90 Your income (in points) 99 98 96 93 89 83 75 65 51 35

Case 2: Assume that A forces you to exert an effort level of at least 2.

Your effort level 1 2 3 4 5 6 7 8 910 Income of A (in points) 16 29 41 53 64 75 82 87 90 Your income (in points) 98 96 93 89 83 75 65 51 35

Case 3: Assume that A forces you to exert an effort level of at least 3.

Your effort level 1 2 3 4 5 6 7 8 910 Income of A (in points) 29 41 53 64 75 82 87 90 Your income (in points) 96 93 89 83 75 65 51 35

Please answer the questions.

4 B Main experiment: Sample details on jobs, dropouts and migrants

B.1 Eliciting job characteristics Before registering for the study, we asked potential participants to only proceed if they were working at that time. In addition, participants were asked in the survey whether they have a regular job: “We are assuming that you are employed. (Employed persons are all persons who are in an employment relationship or who carry out an economic activity as self-employed persons or family workers). The following question now relates to whether you are currently working regularly. Do you currently work regularly? (Please answer “No” if you have more irregular, short-term jobs).” The variables Leader, Job sector and ISCO-08 Skill level as used in Table 3 of the paper are derived from subjects’ answers to the open question “What is your job title? (Please be as precise as possible)” and a description of their job introduced as follows: “The work of two persons with the same job title may differ significantly in terms of their specific tasks, their sectors, and their responsibilities. We would therefore be grateful if you could briefly describe your work from these three points of view.” Subjects’ answers were coded according to the International Classification of Occupations ISCO-08 (International Labour Organization, 2012) by independent raters who were na¨ıve with respect to the aim of the study. The ISCO-08 Skill levels were derived from the ISCO-08 job classifications as defined by the In- ternational Labour Organization. Occupations at Skill level 1 are elementary jobs which require the performance of simple and routine physical or manual tasks (e.g., office cleaners or kitchen assistants). Occupations at Skill level 2 typically involve the performance of tasks such as operating machinery, maintenance and repair of equipment, and manipulation, ordering and storage of information (e.g., secretaries, accounts clerks, or shop sales assistants). Occupations at Skill level 3 typically involve the performance of complex technical and practical tasks which require an extensive body of specialized knowledge (e.g., medical laboratory technicians, legal secretaries, commercial sales representatives, or computer support technicians). Occupations at Skill level 4 typically involve the performance of tasks which require complex problem solving and decision making based on an extensive body of knowledge in a specialized field (e.g., researchers, sales and marketing managers, civil engineers, secondary school teachers, medical practitioners, or computer systems analysts).

B.2 Reasons for dropouts As evident from Table 4 of the paper, a total of 180 non-migrants (95 agents and 85 principals) did not complete 10 rounds with a human partner. The reasons are as follows: We lost choices of 28 non-migrants in one session due to a server crash after the first round. For about 70 non-migrants the final round was canceled (four sessions) or the two final rounds were canceled (two sessions) due to our non-contagion matching procedure as the number of active participants had dropped below 20. 55 non-migrants continued with an artificial partner either because of an odd number of participants after the first round, or because a human partner dropped out during the course of the experiment. We consider choices from interactions with a human but not with an artificial partner. Accordingly, we suffered a loss of approximately 150 consequential dropouts among non-migrants. The large majority of the remaining roughly 30 non-migrants informed our email support that they were kicked out for technical reasons (unstable internet connection, server access denied, incompatibilities of our code with specific combinations of outdated browser versions and operating systems).1 Thus, we are confident to assume that very few participants dropped deliberately and experimental behavior of those who completed ten rounds or not should not differ systematically.

1Less than 5% of the participants suffered technical problems due to our code.

13 B.3 Details about migrants

Educational background

econ social human tech missing

N (Round 1) Female Age mean (sd) Studies Studies Studies Studies Studies

Younger migrants East to West 46 65% 27.84 (1.54) 15% 26% 28% 28% 2% Younger migrants West to East 15 40% 28.01 (1.59) 47% 13% 13% 27% 0% Older migrants East to West 18 67% 37.81 (5.39) 28% 33% 11% 28% 0% Older migrants West to East 21 33% 37.24 (7.66) 5% 38% 29% 29% 0%

Table 1: Characteristics of non-student migrants. Note: These sample characteristics are based on all migrants who participated in at least round 1. The cate- gories of educational background are as follows: Studies econ refers to “business administration & economics”; Studies social refers to “behavioral & social sciences except economics”; Studies human refers to “humanities”; and Studies tech refers to “engineering, life & natural sciences”.

Agents Principals Round 1 Round 10 Round 1 Round 10 Younger German migrants (born in ’80s) East to West 28 19 18 15 West to East 4 1 11 7 Older German migrants (born before ’80) East to West 10 7 8 4 West to East 9 6 12 7

Table 2: Number of migrants among agents and principals in the first and final rounds (interactions with artificial partners excluded).

14 C Main experiment: Complementary data analysis

C.1 Cumulative frequencies of agents’ effort Figure 1 shows the cumulative frequencies of agents’ effort per control level. We observe that the cumulative distribution of efforts under no control is hardly distinguishable between East and West, whereas under low and in particular under medium control efforts lower than seven are made more often in the West than in the East.

No control Low control Medium control 1 1 1

.9 .9 .9

.8 .8 .8

.7 .7 .7

.6 .6 .6

.5 .5 .5

.4 .4 .4

.3 .3 .3 Cumulative frequency Cumulative frequency Cumulative frequency .2 .2 .2

.1 East .1 East .1 East West West West 0 0 0 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 Effort Effort Effort

Figure 1: Cumulative frequency of efforts per control level in East and West.

Figure 2 shows the cumulative frequencies of agents’ effort per control level, separately for older and younger East and West Germans. Among younger East and West Germans (first panel), the cumulative distributions of efforts under no, low and medium control are rather similar. In the older generation (second panel), the most striking difference concerns efforts under medium control where West Germans choose efforts below seven much more often than East Germans.

No control Low control Medium control 1 1 1

.9 .9 .9

.8 .8 .8

.7 .7 .7

.6 .6 .6

.5 .5 .5

.4 .4 .4

.3 .3 .3 Cumulative frequency Cumulative frequency Cumulative frequency .2 .2 .2

.1 Younger East .1 Younger East .1 Younger East Younger West Younger West Younger West 0 0 0 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 Effort Effort Effort

No control Low control Medium control 1 1 1

.9 .9 .9

.8 .8 .8

.7 .7 .7

.6 .6 .6

.5 .5 .5

.4 .4 .4

.3 .3 .3 Cumulative frequency Cumulative frequency Cumulative frequency .2 .2 .2

.1 Older East .1 Older East .1 Older East Older West Older West Older West 0 0 0 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 Effort Effort Effort

Figure 2: Cumulative frequency of efforts per control level for younger and older East and West Ger- mans.

15 C.2 Agents’ effort over time

West East 5 5 4.5 4.5 4 4 3.5 3.5 3 3 Average effort Average effort 2.5 2.5 2 2 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 Round Round

No control Low control Medium control

Figure 3: Average effort over time in East and West.

C.3 Agents’ intrinsic motivation over time

4

3.5

3

2.5

2

1.5

Intrinsic motivation: e(1) 1

.5

0 1 2 3 4 5 6 7 8 9 10 Round West East

Figure 4: Intrinsic motivation over time in East and West.

16 C.4 Agents’ effort differences The models in Table 3 correspond to those in Table 6 of the article and differ only in the dependent variable as we now consider effort differences (instead of control aversion). Models 1 to 3 predict differences between efforts under low and no control, while models 4 to 6 predict differences between efforts under medium and no control.

Dependent variable: Difference between effort under low and no control medium and no control e(2) − e(1) e(3) − e(1) (1) (2) (3) (4) (5) (6) Constant 0.403*** 0.519*** 0.890** 0.731*** 0.619*** 0.950 (0.120) (0.121) (0.432) (0.214) (0.214) (0.764) West -0.234 -0.340** -0.352** -0.364 -0.484* -0.533* (0.147) (0.149) (0.166) (0.266) (0.259) (0.291) Half2 -0.374*** -0.361*** -0.517*** -0.520*** (0.070) (0.069) (0.089) (0.089) West*Half2 0.290*** 0.279*** 0.322*** 0.326*** (0.087) (0.086) (0.109) (0.109) bA(2) − bA(1) 0.007*** 0.007*** (0.001) (0.001) bA(3) − bA(1) 0.005*** 0.005*** (0.001) (0.001) Female 0.018 0.140 (0.146) (0.259) Partner 0.094 0.102 (0.165) (0.293) Childhood north -0.059 0.070 (0.185) (0.326) Later north 0.141 0.202 (0.192) (0.338) Studies human -0.267 -0.509 (0.226) (0.401) Studies tech 0.019 0.046 (0.199) (0.352) Studies social -0.066 0.061 (0.207) (0.365) Trustworthiness -0.054* -0.128** (0.033) (0.058) LifeControl -0.026 0.008 (0.047) (0.083) Observations 2,250 2,250 2,229 2,250 2,250 2,229 Log-likelihood -3442.029 -3413.920 -3344.416 -4043.957 -4014.872 -3961.375 Hypothesis testing East=West in Rounds 1-5 p = 0.022 p = 0.035 p = 0.061 p = 0.067 East=West in Rounds 6-10 p = 0.744 p = 0.669 p = 0.537 p = 0.482 Notes: Standard errors in parentheses. ∗∗∗(1%); ∗∗(5%); ∗(10%) significance level.

Table 3: Determinants of control aversion in East and West.

Averaged over all agents and rounds, among East Germans, effort differences are significantly positive and (insignificantly) more so than among West Germans (models 1 and 4). Still, effort differ- ences are (weakly) significantly positive also in the West (χ2-tests: p − value = 0.067 in model 1 and p − value = 0.025 in model 4). Accordingly, on average, principals earn more when facing agents from either part of Germany if they enforce low or medium control instead of refraining from restrictions. The results of models 2 and 5 show that effort differences among experienced agents are less positive than among inexperienced agents in the East while the decrease is significantly less pronounced in the West. The effect of belief differences is significantly positive (though small), suggesting that the

17 more principals the agent expects to control, the more positively she reacts to control. The inclusion of demographic controls and attitudes towards trust and control has little impact on the estimated coefficients of models 2 and 5. None of the demographics affects effort differences consistently as shown in models 3 and 6. The more an agent expects trustworthiness from strangers, the less she seems to reward control, while control over life does not help to explain effort differences. Finally, the lower panel of Table 3 reports χ2 tests of the equality of linear combinations of coefficients to test whether agents in East and West differ in the first and second halves of the experiment. East-West differences are (weakly) significant in the first half of rounds and they are reduced over time, as indicated by the tests and illustrated in Figure 5. In sum, effort differences are positive in both parts of Germany meaning that disciplining effects outweigh crowding effects of low and medium control. Effort differences are more positive among East than among West Germans, but the differences are reduced over time.

1.5 1.5 1.25 1.25 1 1 .75 .75 .5 .5

e(2) - e(1) .25 .25 e(3) - e(1) 0 0 -.25 -.25 -.5 -.5 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 Round Round

West East

Figure 5: Effort differences over time in East and West.

To test whether East-West differences in the effectiveness of control persist or converge across gen- erations, we compare effort differences in East and West for young professionals (born in the 80s) and elder professionals (born before 1980). As before, we rely on linear mixed models with random intercepts for agents and sessions. Table 4 reports the estimation results. Models 1 and 4 predict effort differences for each subsample (the constant is omitted). Differences between efforts under low or medium control and no control are (weakly) significantly positive for all subsamples except for older West Germans. The lower panel of Table 4 reports χ2 tests on the equality of coefficients to test whether effort differences differ between our cohorts from East and West. Older East Germans increase their effort significantly more with control than older West Germans while we never reject the hypothesis that younger Germans are different between East and West. According to models 2 and 5, effort differences evolve slightly differently for our cohorts. Inexpe- rienced agents increase their effort (qualitatively) more under control than experienced agents from both parts of Germany as the estimated coefficients of all subsamples are smaller in the second than in the first half of rounds. While effort differences of experienced older West Germans are negative, effort differences of experienced older East Germans are still positive. The effect of belief differences is significant but small. Hypothesis testing reveals that effort differences among younger Germans, inexperienced or experienced, never differ significantly between East and West. In contrast, among older Germans, effort differences are significantly more positive in the East than in the West in 3 out of 4 comparisons. Figure 6 complements our estimation results. The outcomes of our hypothesis testing are robust when including demographics and attitudes

18 (models 3 and 6). None of the demographics affects effort differences.2 Optimistic views on trustwor- thiness tend to decrease effort differences, while control over life lacks explanatory power. In a nutshell, among older Germans, East-West differences in effort differences are rather stable. Older East Germans increase their effort under control, while for older West Germans, average effort differences are around zero. We never reject the null hypothesis that effort differences among younger Germans are the same in East and West. As effort differences are never significantly negative, a general advice for a risk averse principal would be to always control the agent. More precisely, control clearly pays for the principal when facing younger West Germans and older East Germans. The picture is less clear for younger East Germans and older West Germans, where it can pay to leave the experienced agent’s choice set unrestricted.

Dependent variable: Difference between effort under low and no control medium and no control e(2) − e(1) e(3) − e(1) (1) (2) (3) (4) (5) (6) Younger East Germans 0.287* 0.404** 0.720 0.531* 0.459 0.646 (0.165) (0.167) (0.452) (0.293) (0.292) (0.793) Younger West Germans 0.253** 0.241** 0.551 0.604*** 0.359* 0.521 (0.118) (0.119) (0.436) (0.210) (0.213) (0.768) Older East Germans 0.522*** 0.638*** 0.962** 0.940*** 0.801*** 1.017 (0.167) (0.169) (0.443) (0.302) (0.299) (0.780) Older West Germans 0.056 0.096 0.398 0.041 -0.155 -0.026 (0.136) (0.137) (0.452) (0.244) (0.242) (0.798) Younger East Germans * Half2 -0.011 0.334 -0.247 -0.072 (0.174) (0.455) (0.301) (0.797) Younger West Germans * Half2 0.198 0.513 0.161 0.323 (0.122) (0.437) (0.218) (0.770) Older East Germans * Half2 0.299* 0.622 0.459 0.676 (0.173) (0.445) (0.305) (0.783) Older West Germans * Half2 -0.045 0.257 -0.344 -0.212 (0.140) (0.453) (0.248) (0.799)

bA(2) − bA(1) 0.007*** 0.007*** (0.001) (0.001) bA(3) − bA(1) 0.005*** 0.005*** (0.001) (0.001) Trustworthiness -0.053 -0.124** (0.033) (0.057) LifeControl -0.025 0.011 (0.047) (0.082) Demographic controls No No Yes No No Yes Observations 2,250 2,250 2,229 2,250 2,250 2,229 Log-likelihood -3440.888 -3412.074 -3342.627 -4041.945 -4010.658 -3956.866 Hypothesis testing East = West in rounds 1-10 Younger Germans p = 0.864 p = 0.840 Older Germans p = 0.028 p = 0.020 East=West in rounds 1-5 Younger Germans p = 0.422 p = 0.434 p = 0.775 p = 0.739 Older Germans p = 0.012 p = 0.015 p = 0.012 p = 0.010 East=West in rounds 6-10 Younger Germans p = 0.320 p = 0.423 p = 0.256 p = 0.302 Older Germans p = 0.120 p = 0.124 p = 0.036 p = 0.031 Notes: Standard errors in parentheses. ∗∗∗(1%); ∗∗(5%); ∗(10%) significance level. The upper four regressors apply to all rounds in models 1 and 4, but only to rounds 1-5 in the remaining models.

Table 4: Determinants of effort differences among cohorts in East and West.

2We consider the same demographic controls as in Table 3. The corresponding details are available from the authors upon request.

19 1.5 1.5 1.25 1.25 1 1 .75 .75 .5 .5 .25 .25 e(2) - e(1) e(3) - e(1) 0 0 -.25 -.25 -.5 -.5 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 Round Round

Younger West Germans Younger East Germans

1.5 1.5 1.25 1.25 1 1 .75 .75 .5 .5 .25 .25 e(2) - e(1) e(3) - e(1) 0 0 -.25 -.25 -.5 -.5 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 Round Round

Older West Germans Older East Germans

Figure 6: Effort differences over time among cohorts in East and West.

20 C.5 Agents’ control aversion in East and West over time

.5 .5

0 0

-.5 -.5

-1 -1 e(2) - max [e(1), 2] e(3) - max [e(1), 3]

-1.5 -1.5

1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 Round Round

West East

Figure 7: Control aversion over time in East and West.

21 C.6 Perceived and desired control and freedom at work To find out whether experiences with control and freedom at work could explain control-related pref- erences in our experiment, we asked subjects for their perceived and desired control and freedom at work with respect to tasks, task execution, and performance control:

Predefined tasks “A job encompasses a variety of tasks. In some jobs these tasks are clearly defined, while in other jobs one is free to shape the content of work. To what extent are your tasks predefined? To what extent would you like to have predefined tasks?” Answers to both questions are provided on Likert scales ranging from 1 (“Fixed regulations”) to 10 (“Absolute freedom”).

Predefined task execution “A task can be executed in different ways. In some jobs the sequence and the execution of tasks is clearly defined. In other jobs one is free to decide about the sequence and the execution of tasks. To what extent is the execution of your tasks predefined? To what extent would you like the execution of your tasks to be predefined?” Answers to both questions are provided on Likert scales ranging from 1 (“Fixed regulations”) to 10 (“Absolute freedom”).

Performance control “When executing your tasks, you exhibit a certain performance level. In some jobs performance is strictly controlled while in other jobs performance is never checked. To what extent is your job performance controlled? To what extent would you like your job performance to be controlled?” Answers to both questions are provided on Likert scales ranging from 1 (“Absolutely no control”) to 10 (“Very strict control”).

Extent of predefined tasks Extent of predefined task execution Extent of performance control 10 10 10 8 8 8 6 6 6 4 4 4 2 2 2 Fixed regulations Absolute freedom Fixed regulations Absolute freedom 0 0 0 Absolutely no control Very strict Younger East Younger West Older East Older West Younger East Younger West Older East Older West Younger East Younger West Older East Older West

Perceived Desired Perceived Desired Perceived Desired

Figure 8: Perceived and desired control and freedom at work among cohorts in East and West.

22 C.7 Robustness of hypotheses 1 and 2: Effort costs of control aversion We test the robustness of the results on Hypotheses 1 and 2 by computing control aversion based on effort costs instead of efforts. To do so, effort levels are translated into their associated effort costs, denoted by c(e). Agents’ effort costs reflect how many points the agent gives up by choosing a certain effort level compared to the lowest effort level of 1. An agent choosing the lowest effort level does not give up any point and receives the maximal payoff of 99 points (c(1) = 0). If she chooses effort level 2, she gives up 1 point and thus, her effort cost equals 1 (c(2) = 1). An agent choosing effort level 3 bears costs of 3 points (c(3) = 3), and so on. Effort costs are non-linearly increasing with the effort level as evident from Table 5.

Effort level 1 2 3 4 5 6 7 8 9 10 Agent’s monetary payoffs 99 98 96 93 89 83 75 65 51 35 Agent’s effort costs c(e) 0 1 3 6 10 16 24 34 48 64

Table 5: Agents’ effort costs by effort level.

Aversion to low control is captured by the differences between effort costs under low control, c(e(2)), and shifted effort costs under no control, max[c(e(1)), c(2)]. Similarly, aversion to medium control is captured by the differences between effort costs under medium control, c(e(3)), and shifted effort costs under no control, max[c(e(1)), c(3)]. The models in Table 6 correspond to those in Table 6 of the article and differ only in how the dependent variable is constructed. Our main results with respect to Hypothesis 1 are confirmed: control aversion is initially significantly stronger among West than among East Germans and the differences are reduced over time. Likewise, the models in Table 7 correspond to those in Table 7 of the article and test whether our results on Hypothesis 2 are robust when relying on effort costs instead of effort levels. Again, the outcomes of these analyses are well in line with our original findings. Most importantly, they confirm that among elder professionals, East-West differences in control aversion largely persist while they converge in our young cohorts.

23 Dependent variable: Aversion to low (vs. no) control in costs medium (vs. no) control in costs c(e(2)) − max[c(e(1)), c(2)] c(e(3)) − max[c(e(1)), c(3)] (1) (2) (3) (4) (5) (6) Constant -0.921 -0.341 1.119 -1.275 -1.739* -0.988 (0.567) (0.580) (2.070) (0.898) (0.941) (3.259) West -1.343* -1.873*** -1.706** -2.122* -2.619** -2.433* (0.704) (0.720) (0.804) (1.124) (1.118) (1.248) Half2 -1.954*** -1.897*** -2.562*** -2.559*** (0.404) (0.402) (0.487) (0.489) West*Half2 1.485*** 1.460*** 1.379** 1.395** (0.501) (0.498) (0.598) (0.601) bA(2) − bA(1) 0.047*** 0.045*** (0.008) (0.008) bA(3) − bA(1) 0.026*** 0.026*** (0.006) (0.006) Female 0.022 0.564 (0.699) (1.101) Partner 0.422 0.893 (0.790) (1.246) Childhood north -0.596 0.320 (0.890) (1.393) Later north 0.570 0.234 (0.920) (1.443) Studies human -1.322 -2.344 (1.078) (1.702) Studies tech 0.064 0.425 (0.951) (1.498) Studies social 0.222 0.883 (0.987) (1.555) Trustworthiness -0.294* -0.586** (0.156) (0.246) LifeControl -0.061 0.076 (0.224) (0.352) Observations 2,250 2,250 2,229 2,250 2,250 2,229 Log-likelihood -7341.896 -7312.870 -7220.362 -7807.772 -7782.875 -7702.086 Hypothesis testing East=West in Rounds 1-5 p = 0.009 p = 0.034 p = 0.019 p = 0.051 East=West in Rounds 6-10 p = 0.605 p = 0.767 p = 0.280 p = 0.415 Notes: Standard errors in parentheses. ∗∗∗(1%); ∗∗(5%); ∗(10%) significance level.

Table 6: Control aversion among East and West Germans (computed based on effort costs).

24 Dependent variable: Aversion to low (vs. no) control in costs medium (vs. no) control in costs c(e(2)) − max[c(e(1)), c(2)] c(e(3)) − max[c(e(1)), c(3)] (1) (2) (3) (4) (5) (6) Younger East Germans -1.790** -1.331* -0.284 -2.666** -2.893** -2.931 (0.784) (0.805) (2.158) (1.244) (1.278) (3.375) Younger West Germans -1.784*** -1.871*** -0.581 -2.431*** -3.523*** -3.167 (0.550) (0.568) (2.075) (0.882) (0.935) (3.259) Older East Germans -0.050 0.663 1.850 0.166 -0.500 -0.273 (0.789) (0.811) (2.109) (1.270) (1.289) (3.308) Older West Germans -2.937*** -2.684*** -1.436 -4.702*** -5.443*** -5.340 (0.636) (0.656) (2.152) (1.023) (1.047) (3.378) Younger East Germans * Half2 -3.189*** -2.013 -6.525*** -6.574* (0.848) (2.180) (1.334) (3.402) Younger West Germans * Half2 -2.081*** -0.736 -4.627*** -4.245 (0.587) (2.081) (0.969) (3.269) Older East Germans * Half2 -1.399* -0.219 -2.080 -1.866 (0.839) (2.122) (1.335) (3.326) Older West Germans * Half2 -3.495*** -2.240 -6.723*** -6.608* (0.676) (2.158) (1.087) (3.389) bA(2) − bA(1) 0.047*** 0.045*** (0.008) (0.008) bA(3) − bA(1) 0.025*** 0.026*** (0.006) (0.006) Trustworthiness -0.284* -0.563** (0.155) (0.243) LifeControl -0.056 0.090 (0.221) (0.347) Demographic controls No No Yes No No Yes Observations 2,250 2,250 2,229 2,250 2,250 2,229 Log-likelihood -7339.772 -7309.976 -7217.194 -7805.121 -7777.740 -7696.455 Hypothesis testing East = West in rounds 1-10 Younger Germans p = 0.995 p = 0.878 Older Germans p = 0.004 p = 0.003 East=West in rounds 1-5 Younger Germans p = 0.582 p = 0.777 p = 0.678 p = 0.884 Older Germans p = 0.001 p = 0.003 p = 0.002 p = 0.003 East=West in rounds 6-10 Younger Germans p = 0.281 p = 0.242 p = 0.225 p = 0.160 Older Germans p = 0.051 p = 0.078 p = 0.005 p = 0.007 Notes: Standard errors in parentheses. ∗∗∗(1%); ∗∗(5%); ∗(10%) significance level. The upper four regressors apply to all rounds in models 1 and 4, but only to rounds 1-5 in the remaining models.

Table 7: Control aversion among younger and older East and West Germans (computed based on effort costs).

25 C.8 Robustness of hypothesis 2: Varying the age cutoff

East West 20

15

10 Frequency

5

0 50 60 70 80 90 50 60 70 80 90 Birth_year Graphs by West Figure 9: Distribution of agents’ year of birth in East and West Germany.

Cutoff year 1977 1978 1979 1980 1981 1982 1983 Aversion to low control East = West in rounds 1-10 Younger Germans p = 0.235 p = 0.271 p = 0.376 p = 0.639 p = 0.612 p = 0.856 p = 0.986 Older Germans p = 0.027 p = 0.020 p = 0.014 p = 0.006 p = 0.008 p = 0.002 p = 0.006 Aversion to medium control East = West in rounds 1-10 Younger Germans p = 0.317 p = 0.376 p = 0.648 p = 0.930 p = 0.604 p = 0.415 p = 0.451 Older Germans p = 0.022 p = 0.016 p = 0.004 p = 0.002 p = 0.001 p = 0.001 p = 0.002 Number of observations Younger East Germans 518 508 440 384 350 291 246 Younger West Germans 1044 974 935 831 693 574 438 Older East Germans 272 282 350 406 440 499 544 Older West Germans 416 486 525 629 767 886 1022

Table 8: Robustness of hypothesis 2 when varying the cutoff year for younger and older Germans. Notes: “Aversion to low control” is based on model 1 and “Aversion to medium control” is based on model 4 of Table 7 in the paper. “Older Germans” were born before the cutoff year and “younger Germans” were born in the cutoff year or later.

26 C.9 Older German migrants To complement our findings on Hypothesis 2, we compare control aversion among migrants and non- migrants in our older cohort. In our sample, we have 10 older agents who migrated from East to West Germany (7 remaining in round 10) and 9 agents who migrated from West to East Germany (6 remaining in round 10).3 This sample size is small and the results should be treated with caution, but at least it gives us an impression. Table 9 reports the regression results from linear mixed models with random intercepts for agents and sessions. Model 1 corresponds to model 1 in Table 7 of the article and model 2 corresponds to model 4 in Table 7 of the article.4 Regression results of models 1 and 2 show that hidden costs of low or medium control are signifi- cantly negative for our older subjects who originated from West Germany, whether they migrated to East Germany or not. By contrast, hidden costs of control are insignificantly different from zero for our older subjects with East German origin, whether they migrated to the West or not. For older East Germans (both migrants and non-migrants), there are even (non-significant) hidden benefits of control. The lower panel of Table 9 reports χ2-tests on the equality of coefficients to test whether control aversion of migrants differs from control aversion of non-migrants in the two parts of Germany. We never reject the null hypothesis that migrants’ control aversion differs from their peers in the part of their origin. However, migrants’ control aversion always differs significantly from their peers in the part of their destination. This is additional evidence in support of our second hypothesis, namely that experiencing a liberal or coercive regime has a long-lasting impact on control-related preferences. Figure 10 complements our estimation results. To simplify comparisons, the upper panel repeats the lower panel of Figure 3 of the main article.

Dependent variable: Aversion to Low control Medium control e(2) − max[e(1), 2] e(3) − max[e(1), 3] (1) (2) Older non-migrant East Germans 0.133 0.067 (0.116) (0.210) Older non-migrant West Germans -0.346*** -0.826*** (0.095) (0.169) Older migrants East to West Germany 0.187 0.204 (0.248) (0.457) Older migrants West to East Germany -0.824*** -1.024** (0.276) (0.498) Observations 1,187 1,187 Log-likelihood -1668.336 -1970.195 Hypothesis testing Older migrants East to West = Older non-migrant East Germans p = 0.842 p = 0.784 Older migrants East to West = Older non-migrant West Germans p = 0.043 p = 0.034 Older migrants West to East = Older non-migrant East Germans p = 0.001 p = 0.043 Older migrants West to East = Older non-migrant West Germans p = 0.100 p = 0.706 Notes: Standard errors in parentheses. ∗∗∗(1%); ∗∗(5%); ∗(10%) significance level.

Table 9: Control aversion among older East and West German migrants and non-migrants.

3We consider as migrants people who spent most of their childhood between 3 and 12 years in one part of Germany and who spent most of their studies and/or time after studies in the other part of Germany. 4We do not perform the regressions on the dynamics as done in Table 7 of the article because of the small sample size.

27 1 1

.5 .5

0 0

-.5 -.5

-1 -1 e(2) - max [e(1), 2] e(3) - max [e(1), 3]

-1.5 -1.5

1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 Round Round

Older East Germans Older West Germans

1 1

.5 .5

0 0

-.5 -.5

-1 -1 e(2) - max [e(1), 2] e(3) - max [e(1), 3]

-1.5 -1.5

1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 Round Round

Older migrants East to West Germany Older migrants West to East Germany

Figure 10: Dynamics of control aversion among older German non-migrants (upper panel) and mi- grants (lower panel).

28 C.10 Dynamics of the reactions to control and agents’ types In a given round, the pair of efforts (e(1), e(2)) captures the agent’s reactions to low (compared to no) control while the pair of efforts (e(1), e(3)) captures the agent’s reactions to medium (compared to no) control. These reactions can be partitioned into four qualitatively distinct categories that are defined in Table 10. We classify reactions to low and medium control separately to acknowledge that agents might react differently to the two control levels. An alternative approach would be to classify agents based on the triplet of efforts (e(1), e(2), e(3)). This approach would only assign agents to the four categories who show the same reaction to low and medium control, while agents who react differently would be unclassified. Our results would be very similar under this approach as 88% of agents’ choices can be classified consistently and only 12% of the effort triplets contain different reactions to low and medium control. Note that for reactions to medium control, the category of the selfish type contains both fully selfish and weakly selfish choices under no control (e(1) < 3). Our results are very similar if we restrict the classification to fully selfish choices under no control (e(1) = 1).

Type Description Behavioral definition Low vs. no control Medium vs. no control Selfish Chooses minimal effort e(1) = 1 ∧ e(2) = 2 e(1) < 3 ∧ e(3) = 3 Control neutral Does not react to control e(1) = e(2) e(1) = e(3) Control averse Crowding out e(1) > e(2) e(1) > e(3) Control prone Crowding in e(1) < e(2) ∧ e(2) > 2 e(1) < e(3) ∧ e(3) > 3

Table 10: A qualitative classification of the reactions to control.

Figure 11 shows the frequency of agents’ choice types over time in East and West. The upper (lower) graph illustrates how agents react to low (medium) compared to no control. Reactions classified as selfish are always most frequent (around 43%) and rather stable over time in both parts of Germany. Control prone behavior is more frequent in the East (19%) than in the West (9%) and occurs less often over time in both subsamples. The share of neutral reactions to control is about 20% in both subsamples and persists across all rounds. Most importantly, control averse choices are robust over time and more frequent in the West (they constitute 20% of choices in the East and more than a quarter in the West). Figure 12 provides more details with respect to our cohorts.

29 Low vs. no control 1

.8

.6

.4

.2

0 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 East West

Medium vs. no control 1

.8

.6

.4

.2

0 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 East West

Selfish Control prone Control neutral Control averse

Figure 11: Frequency of reactions to control over time in East and West.

30 Low vs. no control 1

.8

.6

.4

.2

0 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 Younger East Germans Younger West Germans Older East Germans Older West Germans

Medium vs. no control 1 31 .8

.6

.4

.2

0 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 Younger East Germans Younger West Germans Older East Germans Older West Germans

Selfish Control prone Control neutral Control averse

Figure 12: Frequency of reactions to control over time among cohorts in East and West. The individual stability of agents’ choice types is represented in Figure 13. For each agent, we count the number of rounds in which she makes a selfish (first panel), control averse (second panel), control neutral (third panel) and control prone (fourth panel) choice with respect to low compared to no control (column on the left) and medium compared to no control (column on the right). We plot the cumulative distributions for agents from East and West Germany. The cumulative distributions are very similar for low and medium control and therefore, we do not distinguish between the two in the explanations below. The type of selfish agents is always most common, fairly robust, and slightly more frequent in the West than in the East (first panel). Around 24% of agents in East and West have selfish reactions in all 10 rounds, and 35% (40%) of the agents in the East (West) are selfish in the majority of rounds (i.e., in at least 6 rounds). Yet, about 40% of agents never behave as a selfish type. Control aversion can also be associated with a relatively persistent type, and more so in the West (second panel). Around 12% (16%) of agents in the East (West) show control averse reactions in all 10 rounds, and about 18% (28%) in the East (West) are control averse in the majority of rounds. Roughly 40% of the agents express control aversion in at least one round. The type of control neutral agents exists but is rather rare (third panel). Less than 10% of agents always react neutrally to control, about 18% (15%) of East (West) Germans do so in the majority of rounds, while roughly 40% adopt such a reaction in at least one round. Agents from both parts of Germany are very similar with respect to control neutral choices as the cumulative distributions for East and West nearly coincide. The type of reactions we interpret as control prone is very rare and somewhat more frequent in the East (fourth panel). Around 60% (75%) of our agents in the East (West) never show crowding in, 14% (3%) in the East (West) adopt such a reaction in the majority of rounds, and hardly any agent does so consistently across all rounds. We infer that this behavior appears to be rather noisy and cannot be associated with a stable type. Figures 14 and 15 detail the stability of agents’ choice types for our cohorts in East and West.

To test whether the frequency of types and in particular control aversion differs between East and West, we rely on mixed-effects logistic regressions with fixed effects for each subsample dummy and a random effect for the agent.5 For regressions on control aversion, the dependent variable is a dummy which takes value 1 if the reaction to control is negative and 0 otherwise. Control averse reactions are significantly less frequent among older East Germans than among their peers in the West (χ2- tests on the equality of coefficients: p − value = 0.022 for low control and p − value = 0.027 for medium control), supporting the impression from Figures 12 and 15 (second panel). The probability of expressing control aversion does not differ significantly between younger East and West Germans (χ2-tests on the equality of coefficients: p − value = 0.558 for low control and p − value = 0.492 for medium control), which is in line with Figures 12 and 14. We also perform the same type of regressions for the selfish and control neutral types, and we never find significant differences between cohorts in East and West.6 In sum, the only significant difference with respect to types of agents’ choices concerns older Germans who express control aversion less often in the East than in the West.

5Details on the regressions are available from the authors upon request. In our starting models we also included random effects at the session level. However, since our dependent variable is binary and we have only few observations per agent, many observations are basically identical such that our models do not always succeed to estimate two random effects. Whenever possible, we also compute the model with two random effects and obtain very similar results. If we omit both random effects and conduct a simple logistic regression, we obtain significant differences more often. Accordingly, subsample differences are overestimated when agents’ idiosyncracies are ignored. 6Unfortunately, those regression models fail for the control prone type as there are too few observations.

32 Low vs. no control Medium vs. no control

Selfish Selfish 1 1

.8 .8

.6 .6

.4 .4

.2 .2 Cumulative frequency Cumulative frequency

0 0 0 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 5 6 7 8 9 10 Number of rounds Number of rounds

Control averse Control averse 1 1

.8 .8

.6 .6

.4 .4

.2 .2 Cumulative frequency Cumulative frequency

0 0 0 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 5 6 7 8 9 10 Number of rounds Number of rounds

Control neutral Control neutral 1 1

.8 .8

.6 .6

.4 .4

.2 .2 Cumulative frequency Cumulative frequency

0 0 0 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 5 6 7 8 9 10 Number of rounds Number of rounds

Control prone Control prone 1 1

.8 .8

.6 .6

.4 .4

.2 .2 Cumulative frequency Cumulative frequency

0 0 0 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 5 6 7 8 9 10 Number of rounds Number of rounds

West East

Figure 13: Stability of agents’ types in East and West.

33 Low vs. no control Medium vs. no control

Selfish Selfish 1 1

.8 .8

.6 .6

.4 .4

.2 .2 Cumulative frequency Cumulative frequency

0 0 0 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 5 6 7 8 9 10 Number of rounds Number of rounds

Control averse Control averse 1 1

.8 .8

.6 .6

.4 .4

.2 .2 Cumulative frequency Cumulative frequency

0 0 0 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 5 6 7 8 9 10 Number of rounds Number of rounds

Control neutral Control neutral 1 1

.8 .8

.6 .6

.4 .4

.2 .2 Cumulative frequency Cumulative frequency

0 0 0 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 5 6 7 8 9 10 Number of rounds Number of rounds

Control prone Control prone 1 1

.8 .8

.6 .6

.4 .4

.2 .2 Cumulative frequency Cumulative frequency

0 0 0 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 5 6 7 8 9 10 Number of rounds Number of rounds

Younger West Germans Younger East Germans

Figure 14: Stability of agents’ types among younger East and West Germans.

34 Low vs. no control Medium vs. no control

Selfish Selfish 1 1

.8 .8

.6 .6

.4 .4

.2 .2 Cumulative frequency Cumulative frequency

0 0 0 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 5 6 7 8 9 10 Number of rounds Number of rounds

Control averse Control averse 1 1

.8 .8

.6 .6

.4 .4

.2 .2 Cumulative frequency Cumulative frequency

0 0 0 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 5 6 7 8 9 10 Number of rounds Number of rounds

Control neutral Control neutral 1 1

.8 .8

.6 .6

.4 .4

.2 .2 Cumulative frequency Cumulative frequency

0 0 0 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 5 6 7 8 9 10 Number of rounds Number of rounds

Control prone Control prone 1 1

.8 .8

.6 .6

.4 .4

.2 .2 Cumulative frequency Cumulative frequency

0 0 0 1 2 3 4 5 6 7 8 9 10 0 1 2 3 4 5 6 7 8 9 10 Number of rounds Number of rounds

Older West Germans Older East Germans

Figure 15: Stability of agents’ types among older East and West Germans.

35 Figure 16 shows the frequency of control averse choices among our subsamples of East and West Ger- mans, pooled across all rounds. Control averse choices are choices where the agent chooses a higher effort under no control than under low control (e(1) > e(2), figure on the left), and choices where the agent chooses a higher effort under no control than under medium control (e(1) > e(3), figure on the right). For both low and medium control, averse choices are less frequent among East Germans than among West Germans.

Aversion to low control Aversion to medium control 50 50

40 40

30 30

20 20

10 10 % of control averse choices: e(1) > e(2) % of control averse choices: e(1) > e(3)

0 0 East West East West

Figure 16: Frequency of control averse choices among East and West Germans.

Similarly, Figure 17 shows the frequency of control averse choices among our subsamples of younger and older East and West Germans, pooled across all rounds. For both low and medium control, averse choices are less frequent among older East Germans than among all other subsamples. The frequency of control averse choices among younger agents is rather similar in East and West, while older West Germans show negative reactions to control more often than older East Germans.

Aversion to low control Aversion to medium control 50 50

40 40

30 30

20 20

10 10 % of control averse choices: e(1) > e(2) % of control averse choices: e(1) > e(3)

0 0 East West East West East West East West Younger Older Younger Older

Figure 17: Frequency of control averse choices among younger and older East and West Germans.

36 C.11 Strength of agents’ control aversion Results 1 and 2 might also be driven by stronger negative reactions to control among West Germans compared to East Germans. To test this conjecture, we run regressions similar to those reported in Tables 6 and 7 of the paper, but now we restrict the sample to control averse choices. If at all, we rather find the opposite tendency: pooling both cohorts, control averse East Germans react (weakly significantly) more negatively to the implementation of low control than control averse West Germans (models 1 to 3 of Table 11), but we never reject the null hypothesis that the strength of aversion to medium control differs between East and West (models 4 to 6). Differentiating between cohorts reveals that this inconsistency is driven only by control averse younger East Germans who react more strongly to low control than younger West Germans and mainly in the second half of rounds, while this East-West difference does not generalize to medium control. Control averse older Germans do not differ in the strength of their reactions, no matter whether we consider all ten rounds or the two halves of the experiment (Table 12).

Dependent variable: Aversion to Low control Medium control e(2) − e(1) e(3) − e(1) if e(1) > e(2) if e(1) > e(3) (1) (2) (3) (4) (5) (6) Constant -2.154*** -2.021*** -2.364*** -3.034*** -2.972*** -2.310*** (0.174) (0.187) (0.646) (0.208) (0.221) (0.775) West 0.474** 0.420* 0.415* 0.139 0.104 0.167 (0.211) (0.222) (0.249) (0.254) (0.265) (0.306) Half2 -0.233* -0.208 -0.231* -0.209 (0.139) (0.139) (0.137) (0.140) West*Half2 0.005 -0.012 0.045 0.015 (0.161) (0.161) (0.158) (0.160) bA(2) − bA(1) 0.004** 0.004** (0.002) (0.002) bA(3) − bA(1) 0.002 0.002 (0.001) (0.001) Female -0.323 -0.046 (0.201) (0.264) Partner 0.183 0.247 (0.237) (0.308) Childhood north 0.274 0.108 (0.267) (0.324) Later north -0.209 -0.042 (0.262) (0.331) Studies human 0.289 -0.373 (0.304) (0.395) Studies tech 0.144 -0.204 (0.277) (0.342) Studies social -0.321 -0.132 (0.284) (0.358) Trustworthiness -0.024 -0.151** (0.051) (0.064) LifeControl 0.061 -0.004 (0.061) (0.073) Observations 540 540 534 580 580 572 Log-likelihood -723.076 -714.844 -695.702 -795.541 -791.005 -773.150 Hypothesis testing East=West in Rounds 1-5 p = 0.059 p = 0.096 p = 0.695 p = 0.586 East=West in Rounds 6-10 p = 0.050 p = 0.101 p = 0.574 p = 0.553 Notes: Standard errors in parentheses. ∗∗∗(1%); ∗∗(5%); ∗(10%) significance level.

Table 11: Determinants of the strength of control aversion in East and West.

37 Dependent variable: Aversion to Low control Medium control e(2) − e(1) e(3) − e(1) if e(1) > e(2) if e(1) > e(3) (1) (2) (3) (4) (5) (6) Younger East Germans -2.285*** -2.104*** -2.464*** -3.176*** -3.040*** -2.406*** (0.218) (0.230) (0.676) (0.260) (0.273) (0.794) Younger West Germans -1.641*** -1.603*** -1.966*** -2.712*** -2.680*** -1.959** (0.164) (0.166) (0.647) (0.202) (0.209) (0.770) Older East Germans -1.937*** -1.917*** -2.415*** -2.809*** -2.938*** -2.307*** (0.281) (0.317) (0.677) (0.332) (0.356) (0.788) Older West Germans -1.722*** -1.598*** -2.084*** -3.090*** -3.061*** -2.400*** (0.171) (0.172) (0.643) (0.207) (0.211) (0.762) Younger East Germans * Half2 -2.445*** -2.776*** -3.455*** -2.799*** (0.224) (0.679) (0.275) (0.799) Younger West Germans * Half2 -1.789*** -2.131*** -2.898*** -2.192*** (0.176) (0.650) (0.214) (0.772) Older East Germans * Half2 -1.946*** -2.428*** -2.767*** -2.140*** (0.284) (0.657) (0.343) (0.788) Older West Germans * Half2 -1.865*** -2.351*** -3.215*** -2.551*** (0.178) (0.645) (0.216) (0.765)

bA(2) − bA(1) 0.004** 0.004** (0.002) (0.002) bA(3) − bA(1) 0.002 0.002 (0.001) (0.001) Trustworthiness -0.019 -0.145** (0.051) (0.063) LifeControl 0.064 -0.010 (0.062) (0.072) Demographic controls No No Yes No No Yes Observations 540 540 534 580 580 572 Log-likelihood -722.548 -713.561 -694.544 -794.329 -787.651 -769.808 Hypothesis testing East = West in rounds 1-10 Younger Germans p = 0.018 p = 0.159 Older Germans p = 0.515 p = 0.471 East=West in rounds 1-5 Younger Germans p = 0.076 p = 0.101 p = 0.286 p = 0.231 Older Germans p = 0.377 p = 0.386 p = 0.766 p = 0.833 East=West in rounds 6-10 Younger Germans p = 0.021 p = 0.036 p = 0.102 p = 0.106 Older Germans p = 0.808 p = 0.831 p = 0.265 p = 0.338 Notes: Standard errors in parentheses. ∗∗∗(1%); ∗∗(5%); ∗(10%) significance level. The upper four regressors apply to all rounds in models 1 and 4, but only to rounds 1-5 in the remaining models.

Table 12: Determinants of the strength of control aversion among cohorts in East and West.

38 C.12 Agents’ beliefs Table 13 reports summary statistics on distributions of agents’ beliefs about principals’ choices. In each panel, the first row reports agents’ beliefs averaged across all agents and rounds, and the second row reports standard deviation. Agents’ expected frequencies of no, low and medium control are very similar in East and West (upper part of the table). The medium control level is expected most often and these expectations increase as the session progresses, as illustrated by Figure 18. This finding also applies to the subsamples of younger and older East and West Germans as evident from the lower part of Table 13 and Figure 19. To test whether there are any significant differences in agents’ beliefs between East and West, we rely on linear mixed regression models with random intercepts at the agent and session levels. Not surprisingly, all regression results are clearly insignificant at the 10 percent level.7 We conclude that behavioral differences among agents in East and West are not driven by different expectations about the principals’ behavior.

Control level No Low Medium Obs. % % % East 790 12.22 16.44 71.34 (16.40) (16.06) (26.48) West 1460 13.12 16.08 70.80 (16.44) (15.61) (26.40) Younger East Germans 384 10.25 14.81 74.94 (13.46) (14.70) (23.55) Younger West Germans 831 11.13 14.72 74.15 (14.84) (15.69) (25.66) Older East Germans 406 14.09 17.98 67.93 (18.59) (17.12) (28.59) Older West Germans 629 15.75 17.88 66.37 (18.03) (15.33) (26.75)

Table 13: Agents’ average beliefs about principals’ choices (standard deviation in parentheses).

100 90 80 70 60 50 40 30 20 Expected relative frequency in % 10 0 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 East West No control Low control Medium control

Figure 18: Agents’ beliefs in East and West over rounds.

7Details are available from the authors upon request.

39 100 90 80 70 60 50 40 30 20 Expected relative frequency in % 10 0 1-5 6-10 1-5 6-10 1-5 6-10 1-5 6-10 Younger East Germans Younger West Germans Older East Germans Older West Germans No control Low control Medium control

Figure 19: Agents’ beliefs among cohorts in both halves of the experiment.

40 C.13 Principals’ control decisions Table 14 reports the frequency of each control level chosen by the principals over all rounds. The medium control level is chosen most often in all subsamples and somewhat more so as the session progresses (except for older West Germans) as illustrated by Figure 20.

Control level No Low Medium Obs. % % % East 689 19 13 68 West 1504 17 18 65 Younger East Germans 492 16 13 71 Younger West Germans 897 15 16 69 Older East Germans 197 26 13 61 Older West Germans 607 19 21 60

Table 14: Frequencies of principals’ control levels.

100 90 80 70 60 50 40 30 Relative frequency in % 20 10 0 1-5 6-10 1-5 6-10 1-5 6-10 1-5 6-10 Younger East Germans Younger West Germans Older East Germans Older West Germans No control Low control Medium control

Figure 20: Principals’ choices among cohorts in both halves of the experiment (rounds 1-5 and 6-10).

We test whether principals in East and West behave differently with the help of linear mixed models where the dependent variable is the level of control implemented by the principal and random intercepts at the principal and session levels are included. Table 15 reports the estimation results.8 According to model 1, averaged over all principals and rounds, the estimated control level does not differ significantly between East and West. Moreover, the results of model 2 show that the extent of control increases over time but not significantly so. The higher the effort increase principals expect when imposing medium compared to no control, the higher the control level they impose (the coefficient of bP (3) − bP (1) is significantly positive). Finally, the regression results are robust to the inclusion of demographic controls. The more optimistic principals are about the trustworthiness of others, the less they control. The remaining demographics do not affect the principal’s decision in a meaningful way. Table 16 provides a more detailed analysis by distinguishing between younger and older East and West Germans. As before, we rely on linear mixed models with random intercepts for agents and

8As for the analysis of agents’ effort decisions, the estimate of the random intercept at the session level is basically zero for all regression models of the principals’ control decisions and the same regressions without a random intercept at the session level generate identical standard errors. We obtain the same qualitative findings with ordered probit regressions which take the ordinal structure of control levels into account. Using OLS regressions with standard errors clustered for subjects also gives similar results.

41 Dependent variable: Level of control (1) (2) (3) Constant 2.483*** 2.268*** 2.619*** (0.057) (0.054) (0.168) West 0.008 0.034 0.022 (0.070) (0.065) (0.073) Half2 0.058 0.076* (0.046) (0.046) West*Half2 -0.008 -0.025 (0.055) (0.055) bP (2) − bP (1) 0.032 0.031 (0.020) (0.020) bP (3) − bP (1) 0.124*** 0.124*** (0.014) (0.014) Female -0.040 (0.060) Partner -0.027 (0.066) Childhood north 0.034 (0.079) Later north -0.038 (0.083) Studies human -0.171* (0.095) Studies tech -0.104 (0.078) Studies social -0.076 (0.082) Trustworthiness -0.026** (0.013) LifeControl -0.015 (0.018) Observations 2,193 2,193 2,169 Log-likelihood -2258.324 -2137.907 -2105.586 Notes: Standard errors in parentheses. ∗∗∗(1%); ∗∗(5%); ∗(10%) significance level.

Table 15: Determinants of control intensity.

sessions. We never reject the null hypothesis that the estimated control level of younger or older Germans is the same in East and West (χ2 tests: p − value > 0.10 for both comparisons). This is also true for the first and the second halves of the experiment (model 2). Again, the behavior of younger and older principals never differs significantly between East and West (χ2 tests: p − value > 0.10 for all four comparisons). The more principals expect agents’ effort to increase with medium compared to no control, the more effort they enforce. These results are robust to the inclusion of demographic controls (model 3). To summarize, the estimated control level of younger and older principals does not differ signifi- cantly between the two parts of Germany.

42 Dependent variable: Level of control (1) (2) (3) Younger East Germans 2.535*** 2.334*** 2.720*** (0.067) (0.063) (0.172) Younger West Germans 2.540*** 2.334*** 2.713*** (0.051) (0.048) (0.169) Older East Germans 2.359*** 2.106*** 2.506*** (0.104) (0.097) (0.181) Older West Germans 2.416*** 2.253*** 2.625*** (0.063) (0.059) (0.169) Younger East Germans * Half2 2.374*** 2.783*** (0.067) (0.173) Younger West Germans * Half2 2.415*** 2.797*** (0.051) (0.170) Older East Germans * Half2 2.210*** 2.613*** (0.105) (0.185) Older West Germans * Half2 2.259*** 2.631*** (0.061) (0.169)

bP (2) − bP (1) 0.030 0.030 (0.020) (0.020) bP (3) − bP (1) 0.126*** 0.125*** (0.014) (0.014) Trustworthiness -0.022* (0.013) LifeControl -0.024 (0.019) Demographic controls No No Yes Observations 2,193 2,193 2,169 Log-likelihood -2256.158 -2133.895 -2101.700 Notes: Standard errors in parentheses. ∗∗∗(1%); ∗∗(5%); ∗(10%) significance level. The upper four regressors apply to all rounds in model 1, but only to rounds 1-5 in models 2 and 3.

Table 16: Determinants of control intensity for younger and older East and West Germans.

43 C.14 Principals’ beliefs Table 17 reports summary statistics on distributions of principals’ beliefs about agents’ choices. Prin- cipals correctly expect agents to be intrinsically motivated and they also correctly expect efforts to increase with control. Expected effort significantly increases with the level of control in both East and West (Wilcoxon matched-pairs signed-rank tests: p − value < 0.01 in all four cases). The same result applies to each of the four subsamples (younger and older Germans in East and West, Wilcoxon matched-pairs signed-rank tests: p − values < 0.01). Hence, monetary payoff-maximizing princi- pals should always enforce medium control and on average principals correctly believe that enforcing medium control is the decision which maximizes their monetary payoffs.

Expected effort under No Low Medium Obs. control control control East 689 2.96 3.63 4.28 (2.00) (1.72) (1.62) West 1504 2.98 3.54 4.17 (1.95) (1.52) (1.40) Younger East Germans 492 2.86 3.55 4.14 (1.88) (1.66) (1.48) Younger West Germans 897 2.88 3.47 4.11 (1.85) (1.42) (1.34) Older East Germans 197 3.21 3.84 4.63 (2.25) (1.85) (1.86) Older West Germans 607 3.13 3.64 4.26 (2.08) (1.65) (1.49)

Table 17: Principals’ average beliefs about agents’ choices (standard deviation in parentheses).

Expected average effort under no, low and medium control is very similar in East and West (upper part of the table). The lower part of Table 17 addresses our cohorts. The beliefs among younger Germans are very similar in East and West. Older Germans also have similar expectations in East and West, except for the tendency that older East Germans expect more effort under medium control than older West Germans. To test whether there are any significant differences in principals’ beliefs between East and West, we rely on linear mixed regression models with random intercepts at the principal and session levels. Younger and older cohorts pooled, principals’ expected effort under no and low control does not differ significantly between East and West at the 5 percent level. However, West Germans expect significantly less effort under medium control than East Germans (chi2-test: p − value = 0.043). This result is driven by older Germans who expect significantly less effort under medium control in the West than in the East (chi2-test: p − value = 0.011). The beliefs of older principals with respect to the no and low control levels do not differ significantly between East and West at the 5 percent level. The expectations of younger principals never differ significantly between both parts of Germany (chi2-tests: p − values > 0.10 for all three comparisons). We also consider the temporal patterns of control aversion as expected by the principals, for all cohorts within East and West pooled (Figure 21) as well es for each cohort in East and West (Figure 22). Principals’ expectations in East and West are very similar. Overall, principals expect agents’ efforts to increase more with control than they actually do. In particular, in none of the subsamples, principals expect control aversion. Accordingly, principals’ beliefs do not match agents’ actual control aversion well (for comparison, see Figure 3 of the paper). The fact that principals fail to expect control aversion is hardly surprising since they only observe the agent’s effort level which corresponds to the control level they have chosen. Thus, a principal who chooses a medium control level will never learn that some agents exert more effort in case of no control.

44 1.5 1.5

1 1

.5 .5 (1), 2.5] (1), 3.5] P P 0 0

-.5 -.5 (2) - max [b (3) - max [b P P

b -1 -1 b

-1.5 -1.5 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 Round Round

West East

Figure 21: Expected control aversion in East and West.

1.5 1.5

1 1

.5 .5 (1), 2.5] (1), 3.5] P P 0 0

-.5 -.5 (2) - max [b (3) - max [b P P b -1 -1 b

-1.5 -1.5 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 Round Round

Younger West Germans Younger East Germans

1.5 1.5

1 1

.5 .5 (1), 2.5] (1), 3.5] P P 0 0

-.5 -.5 (2) - max [b (3) - max [b P P b -1 -1 b

-1.5 -1.5 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 Round Round

Older West Germans Older East Germans

Figure 22: Expected control aversion among cohorts in East and West.

45 C.15 Principals’ best replies Figure 23 shows in each round the proportion of principals in East and West who choose the control level which according to their elicited beliefs maximizes their monetary payoffs. Most principals best- reply to their beliefs, and the fraction slightly increases as the session progresses. This general pattern largely applies to our cohorts in East and West as illustrated by Figure 24.

100

90

80

70

60

50

40

30

Principals' best replies in % 20

10 West East 0 1 2 3 4 5 6 7 8 9 10 Round

Figure 23: Frequencies of best-replies in East and West.

46 100

90

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60

50

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Principals' best replies in % 20

10 Younger West Germans Younger East Germans 0 1 2 3 4 5 6 7 8 9 10 Round

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Principals' best replies in % 20

10 Older West Germans Older East Germans 0 1 2 3 4 5 6 7 8 9 10 Round

Figure 24: Frequencies of best-replies among cohorts in East and West.

47 D Robustness experiment with students

D.1 Locations of the robustness experiment Figure 25 shows the geographical location of the four cities, and Table 18 shows attributes of the locations guiding our selection. Within East and within West Germany, the more southern cities Jena and Heidelberg are somewhat smaller, have much more students and overall a younger population, a lower unemployment rate and a higher GDP relative to East or West Germany than the northern cities Magdeburg and Oldenburg. Arguably, the main dimension on which the city pairs differ is whether they have been part of the former GDR or FRG.

Figure 25: Map of the 2x2 student locations in Germany. (Source: European Navigator)

Unemployed West/East North/South Population Students Young GDP ratio

Magdeburg East North 230 000 5% 53% 13.5% 1.3 Oldenburg West North 160 000 7% 69% 9.4% 1.2 Jena East South 100 000 26% 66% 8.6% 1.5 Heidelberg West South 145 000 22% 75% 6.3% 1.4

Table 18: Attributes of the four student locations. Note: Young is the population younger than 25 years divided by the population older than 50 years (N <25/N ≥50). Unemployed refers to the unemployment rate in 2009. GDP ratio is a city’s GDP divided by the GDP of East Germany (for Magdeburg and Jena) or by the GDP of West Germany (for Oldenburg and Heidelberg). (Source: Statistik der Bundesagentur f¨urArbeit; Zahlen, Daten, Fakten: Strukturdaten und -indikatoren; 2010)

Characteristics of the student samples Table 19 shows basic characteristics of the four student subsamples (agents and principals pooled). Despite a few exceptions, gender and educational background categories are well represented, and subjects in the matched East-West subsamples are of similar age. We did our best to recruit student samples which are balanced according to gender and educational background distributions, and to have comparable distributions in the samples from Magdeburg/Oldenburg as well as Jena/Heidelberg.

48 We did not fully succeed as we could not identify non-migrant participants beforehand. In addition, the universities of Magdeburg and Oldenburg have somewhat different profiles in the fields of studies they offer.

Educational background

econ social human tech missing

N (Round 1) Female Age mean (sd) Studies Studies Studies Studies Studies

Magdeburg (East) 64 42% 23.30 (2.24) 38% 27% 6% 30% 0% Oldenburg (West) 77 56% 24.85 (2.28) 38% 10% 35% 17% 0% Jena (East) 71 52% 22.74 (2.53) 28% 18% 21% 32% 0% Heidelberg (West) 68 29% 22.83 (2.27) 29% 18% 21% 32% 0%

Students East 135 47% 23.01 (2.40) 33% 22% 14% 31% 0% Students West 145 43% 23.90 (2.48) 34% 14% 28% 24% 0%

Table 19: Characteristics of included participants. Note: These sample characteristics are based on all non-migrant students who participated in at least Round 1. The categories of educational background are as follows: Studies econ refers to “business administration & economics”; Studies social refers to “behavioral & social sciences except economics”; Studies human refers to “humanities”; and Studies tech refers to “engineering, life & natural sciences”.

D.2 Design and procedures Table 20 gives an overview of our robustness treatments. The students treatments vary in payment scheme, scale of interactions, and knowledge about the scale of interactions. N refers to the number of participants who took part in at least one principal-agent interaction. The same treatment variables were implemented in Magdeburg, Oldenburg, Jena and Heidelberg. In StudentsAllPaid, we rely on a within-subjects random incentive scheme (WRIS) where a randomly selected choice or belief is paid to all subjects. In the two StudentsFewPaid treatments we rely on the same hybrid random incentive scheme (HRIS) as in our main experiment. The different payment schemes are accompanied by changes in conversion rates. In the treatment where all students are paid the conversion rate is such that expected payoffs roughly correspond to standard payoffs in the experimental laboratories of our four cities. In the treatments where few students are paid the conversion rate produces high stakes. StudentsAllPaid differs from the two StudentsFewPaid treatments not only in the payment scheme, but also in the scale of interactions. Interactions take place within the local subject pools in Stu- dentsAllPaid and across the four student subject pools in both StudentsFewPaid treatments. There- fore, to establish whether the payment scheme matters, we first have to find out whether the scale of interactions matters. As we lack an intermediate treatment between the two, we do this check indi- rectly by comparing treatments StudentsFewPaid-1 and StudentsFewPaid-2 which only differ in the knowledge about the scale of interactions. In StudentsAllPaid and StudentsFewPaid-1 participants were just informed that they will interact with other students. In StudentsFewPaid-2 participants were aware that the scale of interactions is national. Concretely, participants of StudentsFewPaid-2 were informed explicitly that they will interact with other students from Jena, Heidelberg, Magdeburg and Oldenburg. We never mentioned East and West explicitly.

49 Participants’ Payment 1 ECU Scale of Knowledge Treatment N Sessions status scheme equals interactions of scale StudentsAllPaid 230 8 Students WRIS e 0.15 Local No Magdeburg 59 2 Oldenburg 61 2 Jena 58 2 Heidelberg 52 2 StudentsFewPaid-1 75 2 Students Hybrid RIS e 2.00 National No Magdeburg 19 2 Oldenburg 16 2 Jena 28 2 Heidelberg 12 2

StudentsFewPaid-2 81 2 Students Hybrid RIS e 2.00 National Yes Magdeburg 22 2 Oldenburg 16 2 Jena 29 2 Heidelberg 14 2 Total 386 12

Table 20: Robustness treatments with students.

Practical procedures We focus below on the procedural differences between our main experiment and the robustness exper- iment. Treatments were conducted between November 2010 and February 2011 with the help of the same internet platform as in our main experiment. Participants were students from the universities of Oldenburg, Magdeburg, Heidelberg and Jena who have agreed to participate in economic experiments and were invited using the ORSEE recruitment system (Greiner, 2015).9 Participants received an invitation email via ORSEE with a link (session token) to the registration pages. On these pages participants were informed about the conditions of participation. Before regis- tering, participants in all treatments knew about the payment conditions. Participants of StudentsAll- Paid were informed that expected earnings are the usual ones. Participants of StudentsFewPaid-1 and StudentsFewPaid-2 were informed that 4 winners would be paid a minimum of 62 euros and a maximum of 258 euros and that all the other participants would not be paid. In all treatments but StudentsAllPaid, the number of participants was unrestricted and we never announced estimates about the number of participants. The participation process in all treatments was largely identical to the one described in Subsec- tion 3.1 of the paper. The payment procedures were as follows: Once the choice or belief relevant for payment was determined, participants received another email with a link. In treatment StudentsAll- Paid, this link directed them to a page showing their final payoff and participants received their earnings at their local experimental laboratory. We informed participants that they would receive 2.50 euros as a compensation fee for collecting their earnings. In the two StudentsFewPaid treat- ments, this link directed participants to a page showing their potential payoff followed by a page with lucky numbers between 000 and 999. Each participant could select five lucky numbers, and each lucky number could only be selected once.10 In each lottery, two winners were those whose lucky numbers matched the last three digits (including the two decimal places) of the DAX at the close of trading on two preannounced dates in the future, and a link to an official trading page where participants could

9These data would not have been collected without the great support of Bernhard Kittel and Jan Lorenz from the Experimental Lab of the Center for Social Science Methodology at the university of Oldenburg, Joachim Weimann and Harald Wypior from the MaXLab at the university of Magdeburg, and Christiane Schwieren and Andrew Isaak from the AWI lab at the university of Heidelberg who gave us convenient access to their subject pools. 10The number of lucky numbers a participant could choose was determined by the final number of participants in a lottery.

50 track the DAX was provided. The two participants who interacted with the winners in the selected round also became winners. The earnings were transferred to the bank accounts of the winners af- ter their eligibility was checked. Average payment in StudentsAllPaid was 14.27 euros. In the two StudentsFewPaid treatments the four winners earned on average 125 euros.

D.3 Students’ behavior in East and West Germany For the following analyses, we restrict our data analyses to non-migrants meaning students who spent their childhood, their youth and their studies either only in West Germany or only in East Germany. Moreover, for the sake of consistency with our previous analyses, we exclude students who were born before 1980. Only choices directed at a human partner are considered. We first discuss agents’ efforts and then analyze control aversion among students in East and West.

Agents’ effort among students in East and West Table 21 reports summary statistics of agents’ effort levels for our four student locations. In each panel, the first row reports the average effort for each control level, and the second row reports standard deviation followed by the 1st quartile followed by the median followed by the 3rd quartile for each control level. The numbers of observations reflect the numbers of choices of all agents across rounds.

Control level Obs. No Low Medium Magdeburg (East) 320 2.65 3.32 3.84 (2.51;1;1;4)(1.93;2;2;4)(1.52;3;3;4) Oldenburg (West) 420 2.89 3.26 3.71 (2.50;1;1;5)(1.83;2;2;4)(1.45;3;3;3) Jena (East) 327 2.94 3.31 3.73 (2.29;1;2;5)(1.63;2;2;4)(1.40;3;3;4) Heidelberg (West) 286 3.28 3.43 3.64 (2.66;1;1;6)(1.85;2;2;5)(1.24;3;3;4)

Table 21: Agents’ efforts as a function of the principal’s control level for students. Note: In each panel, the first row reports the average effort for each control level. The second row reports standard deviation followed by 1st quartile followed by median followed by 3rd quartile for each control level.

For each of our matched city pairs Magdeburg/Oldenburg and Jena/Heidelberg, average efforts in the no-control condition are slightly lower in the East than in the West and comparable in the low-control condition, while average efforts in the medium-control condition tend to be slightly higher in the East than in the West. Accordingly, average effort increases somewhat more with control in the East than in the West, as illustrated graphically in Figure 26. The overall impression is that control is most effective in Magdeburg and least effective in Heidelberg. The pattern of average efforts in Oldenburg and Jena appears to be very similar.

Control aversion among students in East and West Table 22 reports regression models to test whether control aversion differs between our matched student locations in East and West. We rely on linear mixed models where random intercepts for the agent are included. According to models 1 and 4, aversion to low and medium control tends to be stronger in the two Western cities than in the two Eastern cities. However, hypothesis testing reveals that this tendency is never significant at the 5 percent level for the matched city pairs Magdeburg/Oldenburg and Jena/Heidelberg (lower part of Table 22). The same conclusion holds for experienced agents

51 Means and 95% confidence intervals 4

3

2

1 Agents' effort level (mean)

0 Magdeburg (East) Oldenburg (West) Jena (East) Heidelberg (West) (320 obs.) (420 obs.) (327 obs.) (286 obs.)

No control Low control Medium control

Figure 26: Average effort levels for the four student locations.

(models 2 and 5 and the corresponding hypotheses tests) and is robust with respect to demographic controls (models 3 and 6). Figure 27 complements our estimation results.

.5 .5

0 0

-.5 -.5

-1 -1 e(2) - max [e(1), 2] e(3) - max [e(1), 3]

-1.5 -1.5

1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 Round Round

Oldenburg (West) Magdeburg (East) Heidelberg (West) Jena (East)

Figure 27: Control aversion over time in the four student locations.

For the sake of completeness, we also perform cross-comparisons of the two non-matched city pairs Magdeburg (East)/Heidelberg (West), and Jena (East)/Oldenburg (West). The results are reported in the bottom of Table 22. On the one hand, we observe systematic differences between students from Magdeburg and Heidelberg as aversion to both low and medium control is significantly more negative in Heidelberg. However, these differences vanish in the second half of rounds when agents gain experience. On the other hand, none of the comparisons suggests that control aversion differs between students from Jena and Oldenburg. Had we considered only students from Magdeburg and Heidelberg, our conclusion would have been ‘still different after all these years’ (Brosig-Koch et al., 2011), whereas the mere comparison of students from Jena and Oldenburg would have supported ‘good-bye Lenin’ (Alesina and Fuchs-Sch¨undeln,2007). These different findings emphasize the methodological value of selecting comparable locations (as far as possible), considering more than one location within a given culture, and relying on repetitions in cross-cultural research. Taken together, control aversion never differs between East and West in three out of four city comparisons. In one (non-matched) city comparison, we observe more control aversion in the West

52 Dependent variable: Aversion to Low control Medium control e(2) − max[e(1), 2] e(3) − max[e(1), 3] (1) (2) (3) (4) (5) (6) Magdeburg (East) 0.044 0.200 0.052 -0.091 0.349 1.019* (0.112) (0.123) (0.278) (0.217) (0.239) (0.547) Oldenburg (West) -0.206** -0.163 -0.292 -0.349* -0.143 0.714 (0.097) (0.106) (0.276) (0.188) (0.205) (0.541) Jena (East) -0.141 -0.169 -0.287 -0.275 -0.069 0.728 (0.111) (0.121) (0.285) (0.214) (0.229) (0.556) Heidelberg (West) -0.363*** -0.412*** -0.499* -0.774*** -0.639*** 0.126 (0.116) (0.126) (0.282) (0.220) (0.235) (0.550) Magdeburg * Half2 -0.125 -0.272 -0.159 0.516 (0.123) (0.278) (0.244) (0.550) Oldenburg * Half2 -0.272** -0.402 -0.260 0.588 (0.107) (0.277) (0.210) (0.543) Jena * Half2 -0.132 -0.250 -0.230 0.573 (0.121) (0.285) (0.234) (0.558) Heidelberg * Half2 -0.332** -0.422 -0.643*** 0.126 (0.129) (0.284) (0.242) (0.554)

bA(2) − bA(1) 0.002 0.002 (0.002) (0.002) bA(3) − bA(1) -0.003** -0.003** (0.001) (0.001) Female 0.080 -0.163 (0.110) (0.216) Partner -0.014 -0.188 (0.107) (0.210) Studies human 0.098 -0.151 (0.149) (0.292) Studies tech -0.282** -0.558** (0.134) (0.261) Studies social 0.242 0.368 (0.162) (0.316) Trustworthiness -0.043* -0.148*** (0.024) (0.048) LifeControl 0.042 0.024 (0.030) (0.059) Observations 1,353 1,353 1,343 1,353 1,353 1,343 Log-likelihood -1885.703 -1878.722 -1859.606 -2212.890 -2197.884 -2176.180 Hypothesis testing: East = West Matched city pairs Magdeburg = Oldenburg in rounds 1-10 p = 0.0929 p = 0.3690 Magdeburg = Oldenburg in rounds 6-10 p = 0.3664 p = 0.4267 p = 0.7389 p = 0.8106 Jena = Heidelberg in rounds 1-10 p = 0.1646 p = 0.1041 Jena = Heidelberg in rounds 6-10 p = 0.2590 p = 0.3142 p = 0.2020 p = 0.1498 Add-on: Non-matched city pairs Magdeburg = Heidelberg in rounds 1-10 p = 0.0115 p = 0.0271 Magdeburg = Heidelberg in rounds 6-10 p = 0.2442 p = 0.3867 p = 0.1385 p = 0.2175 Jena = Oldenburg in rounds 1-10 p = 0.6599 p = 0.7961 Jena = Oldenburg in rounds 6-10 p = 0.3882 p = 0.3358 p = 0.9209 p = 0.9578 Notes: Standard errors in parentheses. ∗∗∗(1%); ∗∗(5%); ∗(10%) significance level.

Table 22: Control aversion in the student cities in East and West.

than in the East, but only in the beginning of the experiment. Thus, students’ choices confirm that the influence of state coercion on control aversion is only short-lived.11 The potential impact of different

11Results on principals’ choices and the beliefs of both roles are as follows. The medium control level is chosen most often in all locations and even more so as the session progresses. Student principals in the East enforce higher effort levels than in the West. Agents’ beliefs largely match principals’ behavior, as the large majority of agents in all locations expects principals to impose medium control and these expectations increase as the session progresses. Agents in Magdeburg expect more restrictions than agents in Oldenburg, while agents’ expected frequencies of no, low and medium control are

53 past regimes is not stronger than the impact of a combination of other attributes like those reported in Table 18 of Appendix D.1, or others unknown to us.

D.4 Students’ behavior in the methodological treatments In terms of payment scheme and (known) scale of interactions, our three methodological treatments introduced in Appendix D.2 are incremental variations from the laboratory to our main experiment. Indeed, treatment StudentsAllPaid uses the payment scheme and scale of interactions that usually prevail in the laboratory and treatment StudentsFewPaid-2 uses the payment scheme of our main experiment and known scale of interactions. Treatments StudentsAllPaid and StudentsFewPaid-1 not only differ in the payment scheme, but also in the scale of interactions. Interactions take place within the local subject pools in StudentsAllPaid and across the four student subject pools in both Students- FewPaid treatments. Therefore, to establish whether the payment scheme matters, we first have to find out whether the scale of interactions matters. As we lack an intermediate treatment between the two, we do this check indirectly by comparing treatments StudentsFewPaid-1 and StudentsFewPaid-2 which only differ in the knowledge about the scale of interactions. Data analyses in this subsection rely on all subjects who participated in the respective treatments, interactions with artificial partners excluded. To test whether there are significant differences between the methodological treatments, we rely on linear mixed regression models with random intercepts on the level of subjects.12

Agents’ effort in the methodological treatments Table 23 shows summary statistics of agents’ effort levels for the methodological treatments (for a graphical illustration, see Figure 28). The numbers of observations reflect the numbers of choices of all agents across rounds.

Control level Obs. No Low Medium StudentsFewPaid-1 360 2.86 3.34 3.66 (2.54;1;1;5)(1.88;2;2;5)(1.31;3;3;4) StudentsFewPaid-2 390 2.85 3.27 3.72 (2.42;1;1;5)(1.78;2;2;4)(1.45;3;3;3) StudentsFewPaid 750 2.86 3.31 3.69 (2.48;1;1;5)(1.83;2;2;4)(1.38;3;3;3) StudentsAllPaid 1,105 2.77 3.21 3.74 (2.44;1;1;5)(1.79;2;2;4)(1.44;3;3;4)

Table 23: Agents’ efforts as a function of the principal’s control level in the methodological treatments. Note: In each panel, the first row reports the average effort for each control level. The second row reports standard deviation followed by 1st quartile followed by median followed by 3rd quartile for each control level.

In StudentsFewPaid-1 and StudentsFewPaid-2, both the average and median effort levels are very similar for each of the three control levels. Regression coefficients of the two treatments do not differ significantly at the 10 percent level for each of the three control levels. Accordingly, the scale of interactions does not seem to affect choices as knowing about it or not makes little difference, and we pool these two treatments resulting in StudentsFewPaid. To find out about the behavioral impact of the payment scheme, we now compare StudentsFewPaid and StudentsAllPaid. Again, average efforts very similar in Jena and Heidelberg. Principals in the two East German locations expect lower effort in the absence of control than principals in the two West German locations, while the expected effort increases with the control level in all locations. Details are available from the authors upon request. 12We do not include random session effects because we have too few sessions per treatment to do so. Details on regressions not reported here are available from the authors upon request.

54 Means and 95% confidence intervals 4

3

2

1 Agents' effort level (mean)

0 StudentsAllPaid StudentsFewPaid-1 StudentsFewPaid-2

No control Low control Medium control

Figure 28: Average effort levels in the methodological treatments.

under no, low and medium control are very similar, and quartiles are nearly identical for each of the three control levels in the two treatments. Our descriptive statistics suggest that the payment scheme does not affect agents’ average efforts, which is again supported by regression results.

Control aversion in the methodological treatments Table 24 reports four regression models to test whether the scale of interactions or the payment scheme affect control aversion. Models 1 and 3 compare the treatment StudentsFewPaid-2 with StudentsFewPaid-1, which is represented by the constant. Knowing about the scale of interactions has no significant impact on control aversion. Thus, we pool both treatments and test whether control aversion in the treatments StudentsFewPaid differs from StudentsAllPaid (represented by the con- stant) in models 2 and 4. Paying all subjects or paying only few subjects does not affect control aversion. We conclude that neither the scale of interactions nor the payment scheme has a meaningful impact on students’ reactions to control.

Dependent variable: Aversion to Low control Medium control e(2) − max[e(1), 2] e(3) − max[e(1), 3] (1) (2) (3) (4) Constant -0.094 -0.152*** -0.422** -0.247** (0.128) (0.059) (0.210) (0.108) StudentsFewPaid-2 -0.063 0.098 (0.177) (0.293) StudentsFewPaid 0.027 -0.124 (0.092) (0.169) Observations 750 1,855 750 1,855 Log-likelihood -1034.325 -2458.933 -1247.834 -2913.818 Notes: Standard errors in parentheses. ∗∗∗(1%); ∗∗(5%); ∗(10%) significance level.

Table 24: Control aversion in the methodological treatments. Note: In models 1 and 3, the constant refers to treatment StudentsFewPaid-1, while in models 2 and 4, the constant captures treatment StudentsAllPaid.

This conclusion also applies to principals’ choices and the beliefs of both roles. Neither the scale of interactions nor the payment scheme affect principals’ choices or agents’ and principals’ beliefs in a meaningful way as we never reject the null hypothesis at the 10 percent level. We conclude that neither the scale of interactions nor the payment scheme affect agents’ or principals’ behavior or beliefs.

55 References

Alesina, A. and Fuchs-Sch¨undeln,N. (2007). Good-bye Lenin (or not?): The effect of communism on people’s preferences. American Economic Review, 97(4):1507–1528.

Brosig-Koch, J., Helbach, C., Ockenfels, A., and Weimann, J. (2011). Still different after all these years: Solidarity behavior in East and West Germany. Journal of Public Economics, 95(11-12):1373–1376.

Greiner, B. (2015). Subject pool recruitment procedures: Organizing experiments with ORSEE. Journal of the Economic Science Association, 1(1):114–125.

International Labour Organization (2012). International Standard Classification of Occupations ISCO- 08: Structure, group definitions and correspondence tables. Geneva: ILO.

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