ARTNeT Greater Mekong Sub-region (GMS) initiative Session 7 Introduction to important statistical techniques for competitiveness analysis – example and interpretations ARTNeT Consultant Witada Anukoonwattaka, PhD Thammasat University, Thailand [email protected] Asia‐Pacific Research and Training Network on Trade 1 www.artnetontrade.org Outline • Concepts of data analysis • Basic data analysis: – Interpreting quantitative and qualitative data • Technical tools – Statistic analysis – Regression • Concepts and interpretation of basic regression analysis Asia‐Pacific Research and Training Network on Trade 2 www.artnetontrade.org What is data analysis? 1. Describing what is going on in the dataset E.g. You explore the sample to find out – the level and changes in relative price competitiveness of the observed garment producers on average. – differences in the cost competitiveness among firm groups, such as • purely-national firms vs. foreign joint-ventures • small vs. large firms Asia‐Pacific Research and Training Network on Trade 3 www.artnetontrade.org 2. Testing hypothesis E.g. You may want to know – Whether the changes in relative cost of Chinese garments to that of the GMS group systematically related to tariff reductions? – Does the changes in relative costs differ systematically between countries in the group? – Are the trends of competitiveness similar between exports to the US and Japanese markets? Asia‐Pacific Research and Training Network on Trade 4 www.artnetontrade.org 3. Forecasting • Can exchange rate depreciation increase export competitiveness of GMS countries to China? By how much? • Can tariff reductions enhance export competitiveness of GMS countries? To what extent? Asia‐Pacific Research and Training Network on Trade 5 www.artnetontrade.org Describing what is going on in the data Asia‐Pacific Research and Training Network on Trade 6 www.artnetontrade.org Interpreting Quantitative Data (1) 1. Overall Average Scores - high or low? Very high or very low scores might mean that the question is poorly worded. 2. Standard Deviations - A low standard deviation means respondents generally had a common response. A high standard deviations mean they had different responses. 3. The frequency distribution will help you get a better idea of what is happening. • Is there any bi-modal distribution where there are two different groups who had very different responses? • Bi-modal distribution might show up as having a normal average score, but high standard deviations. Asia‐Pacific Research and Training Network on Trade 7 www.artnetontrade.org Interpreting Quantitative Data (2) 4. Compare the results between the different demographic subgroups. – Especially focusing on the items where you had interesting things happening in the frequency distributions. 5. If you are serious about understanding your numeric data, you should also perform some statistical analyses. Asia‐Pacific Research and Training Network on Trade 8 www.artnetontrade.org Interpreting Qualitative Data 1. Read through all the comments. Get a feeling for what people are saying. 2. Categorize the comments into different areas. 3. Look at each category separately. How many unique comments are in each? How detailed are those comments? How strongly are they stated? At this point, you should be able to identify which categories are more important and which are less important. 4. Look at the different subgroups to see if any relationships emerge between subgroups and categories of comments. Asia‐Pacific Research and Training Network on Trade 9 www.artnetontrade.org Technical Data Analysis: • Statistic analysis • Hypothesis testing • Forecasting Asia‐Pacific Research and Training Network on Trade 10 www.artnetontrade.org Statistic Analysis 1. Analysis of individual variables – Look at the “central tendency”, “distribution” and “dispersion” of responses to each data variable. 2. Analysis of relationships between variables – Look at “possible interdependence” between data variables. 3. Analysis of difference characteristics between subgroups. – Look at “characteristic differences” between subgroups. Asia‐Pacific Research and Training Network on Trade 11 www.artnetontrade.org Examples What are we analyzing when we investigate a competitiveness survey dataset to find out… a) Whether foreign investment tends to enhance labor productivity of the garment industry? b) Whether export-oriented industries have higher labor productivity than import-competing industries? c) How productive is labor in the garment industry ? Asia‐Pacific Research and Training Network on Trade 12 www.artnetontrade.org Descriptive Statistics Activity Statistics Worker Industry 1 2 3 4 AFTA Foreign Mean 58.75 2 0.33 0.50 0.25 0.42 1 0.58 Standard Error 13.50 0.28 0.14 0.15 0.13 0.15 0.33 0.15 Median 45 2 0 0.5 0 0 1 1 Mode 30 2 0 1 0 0 2 1 SD 46.76 0.95 0.49 0.52 0.45 0.51 1.13 0.51 Minimum 15 1 0 0 0 0 -1 0 Maximum 180 4 1 1 1 1 2 1 Sum 705 24 4 6 3 5 12 7 Count 12 12 12 12 12 12 12 12 Asia‐Pacific Research and Training Network on Trade 13 www.artnetontrade.org Note: You can do descriptive statistics in Excel • Go to menu Tools – Add Ins – check the Analysis Tool pack and then press OK button. Next time when you open the Tools menu again, you will see Data Analysis in the bottom of Tools menu. • Click menu Tools – Data Analysis and you will see Data Analysis dialog. Scroll down and you will see Descriptive Statistics. Select it and click OK button. Asia‐Pacific Research and Training Network on Trade 14 www.artnetontrade.org • You will get the Descriptive Statistics dialog form. In the Input range, select range of your data that you want to be analyzed. Include the label in the first row and check that check box. Check also the Summary statistics check box and then click OK button. Asia‐Pacific Research and Training Network on Trade 15 www.artnetontrade.org The result of the descriptive statistics tool, after formatting, is shown in the figure below. Asia‐Pacific Research and Training Network on Trade 16 www.artnetontrade.org Analyzing Individual Variables • Central tendency of the data • Distribution of the data • Dispersion of the data Asia‐Pacific Research and Training Network on Trade 17 www.artnetontrade.org Tools for Measuring Central Tendency: Mode, Median, Mean • Mode is the most frequently occurring value, • Median is the middle value, • Mean is the average value. Notes: a “Yes” means the indicator is suitable for the measurement level shown. b May be OK in some circumstances. See Example 2. Asia‐Pacific Research and Training Network on Trade c May be misleading when the distribution is asymmetric or has a few 18 outliers. www.artnetontrade.org Competitiveness Analysis Examples: Example 1: Which measures of central tendency to use to find the following information from your dataset? a) Unit labor cost of firms in the footwear industry b) The majority of foreign investors in the textile industry c) Average export ratio when the dataset shows that Firm No. Export ratio 1 20% 2 24% 3 28% 4 30% 5 85% Asia‐Pacific Research and Training Network on Trade 19 www.artnetontrade.org Example 2. The following ordinal scale data shows customers’ views on the quality of domestically produced garments (sample size is 30). Is it possible to find the “mean” of this ordinal variable? Asia‐Pacific Research and Training Network on Trade 20 www.artnetontrade.org Analyzing Data Dispersion: ‘Range’ and ‘Standard Deviation (SD)’ Dispersion is the spread of the values around the central tendency. Range = Max-Min SD = Asia‐Pacific Research and Training Network on Trade Note: All statistic programs (event Excel) re capable of calculating descriptive21 statistics for you. www.artnetontrade.org Analyzing Data Distribution: A Frequency Distribution The frequency distribution is a summary of the frequency of individual values or ranges of values for a variable. A Frequency Distribution of Age Groups Asia‐Pacific Research and Training Network on Trade 22 www.artnetontrade.org Normal Distribution We usually expect normal distribution of the data observations if we performed random sampling. Normal Distribution -1 SD 1 SD -2 SD 2 SD If the mean of our example is 20.5 and the standard deviation is 7.5, we can estimate that approximately 95% of the scores will fall in the range of 20.5-(2*7.5) to 20.5+(2*7.5) or between 4.5 and 35.5 Asia‐Pacific Research and Training Network on Trade 23 www.artnetontrade.org Analyzing Relationships between Variables • Scattered-plot diagram • Cross tabulation (Pivot Table) • Regression analysis Asia‐Pacific Research and Training Network on Trade 24 www.artnetontrade.org Relationships between Variables Is there any relationship between the two variables shown in the scattered-plot diagram? Asia‐Pacific Research and Training Network on Trade 25 www.artnetontrade.org Cross Tabulation (Pivot Table) Attitude toward QC Export orientation Low Medium High Total Indifferent 27 37 56 120 Somewhat positive 35 39 41 115 Positive 43 33 30 106 Total 105 109 127 341 Note: Some statistician called it Contingency Table, while MS excel calls it Pivot Table. Asia‐Pacific Research and Training Network on Trade 26 www.artnetontrade.org Interpretation (1) Attitude toward QC Export orientation Low Medium High Total Indifferent 120 35% Distribution of attitude Somewhat positive 115 34% variable. Positive 106 31% Total 105 109 127 341 100% 100% Distribution of export-orientation variable. Does the sample bias toward particular attitude? Does the sample bias toward particular firm types? Asia‐Pacific Research and Training Network on Trade 27 www.artnetontrade.org Interpretation (2) Attitude toward Export orientation QC Low Medium High Total Indifferent 56 Distribution Somewhat positive 41 of attitudes for Positive 43 33 30 106 high export Total 127 firms. Distribution of export-orientation for positive attitude toward QC. • Is attitude toward QC associated with export orientation of the firms? • Do the firms with a positive attitude toward QC tend to be low or high export-orientation firms? Asia‐Pacific Research and Training Network on Trade • Do the firms with high export-orientation tend to be positive or 28 indifferent toward QC? www.artnetontrade.org Analysis of Differences between Groups E.g.