INFORMAL EMPLOYMENT AND LIFE AND JOB SATISFACTION: A STATISTICAL ASSOCIATION ANALYSIS

1. INFORMAL EMPLOYMENT AND LIFE AND JOB SATISFACTION: A STATISTICAL ASSOCIATION ANALYSIS ALİ BERKER June 5, 2014

2. WHAT THIS STUDY DOES • Estimate the impacts of informal employment on life and job satisfaction. • Explore the monetary value of informal employment.

3. WHAT THIS STUDY DOES • Evaluate differences in life and job satisfaction between informal and formal employment. • Provide evidence for whether informal employment is a matter of choice or not. • Testhypotheses proposed by Perfect Competitive Approach and Segmented Market Approach.

4. MAIN CONTRIBUTIONS OF THIS STUDY • For Turkey, it is the first study to explore the relationship between informal employment and satisfaction measures. • It shows possible ways through which Turkey Life Satisfaction Survey can be used to explore various public policy issues. • Emphasize differences between the association analysis and causality analysis.

5. MAIN FINDINGS Among salaried workers: • It appears that informal employment is negatively related to life and job satisfaction measures. • This negative relation seems to be weak for • Women • University graduates • 50-64 age group

6. STRUCTURE OF PRESENTATION • The relevance of informal employment and well-being production function • Theoretical approaches • Previous studies • Empirical methodology • Estimation results • Conclusion

7. RELATIVE SHARES OF EMPLOYMENT BY INFORMALITY STATUS

8. FORMAL AND INFORMAL EMPLOYMENT (In thousands)

9. THE RELEVANCE OF INFORMAL EMPLOYMENT During 2000-2013, about one-half of Turkey’s population had been directly or indirectly affected by informal employment (per year). • Directly affected population: 10 million • Indirectly affected popuation: 30 million.

10. THE RELEVANCE OF INFORMAL EMPLOYMENT • All countries experience some forms of informal employment. • Informal employment becomes a permanent feature of capitalist economy.

11. THE RELEVANCE OF INFORMAL EMPLOYMENT

12. THE RELEVANCE OF WELL-BEING PRODUCTION FUNCTION Why do we care about the well-being (happiness-satisfaction) production function? Because people with high well-being are  more productive  more healthy. And they are more likely to have  higher income  better and longer marriages longer life spans.

13. RESEARCH QUESTION When changing structure of informal emploment is taken into acount, a critical public policy question emerges: What are the well-being consequences of informal employment?

14. RESEARCH QUESTION

15. THEORETICAL APPROACHES

16. THEORETICAL APPROACH

17. PREVIOUS STUDIES

18. PREVIOUS STUDIES

19. PREVIOUS STUDIES

20. PREVIOUS STUDIES

21. DATA

22. THE CONSTRUCTION OF THE ANALYSIS SAMPLE

23. DEPENDENT VARIABLES LIFE SATISFACTION All things considered, how happy are you with your life overall? 1= Very unhappy 2= Unhappy 3= Neither unhappy nor happy 4= Happy 5= Very happy

24. DEPENDENT VARIABLES

25. DEPENDENT VARIABLES

26. MAIN INDEPENDENT VARIABLE INFORMAL SALARIED WORKER If the individual is working and not registered to social security, she is defined as an informal salaried worker.

27. OTHER INDEPENDENT VARIABLES • Demographic variables Gender, Age (with age squared) • Socieconomic variables Education Marital status Household Income

28. OTHER INDEPENDENT VARIABLES • Socioeconomic variables Health index Household size Proportion of dependent household members Urban status Industries

29. REGRESSION ANALYSIS Define a function that relates the self-reported satisfaction to the real satisfaction: Y: Self-reported satisfaction g(.): Real satisfaction M: Household Income EMP: Binary variable for informality status X: Demographic and socieconomic variables

30. REGRESSION ANALYSIS Regression equation: β2 is the coefficient of interest, measuring the association between informal employment and satisfaction measures. Sampling weights are used. Standard errors are clustered by years.

31. REGRESSION MODELS

32. ESTIMATION METHODS

33. ESTIMATION METHODS

34. ASSOCIATION VS. CAUSALITY ANALYSIS A cross-sectional analysis suffers from four main problems that lead to the endogeneity of the informality status in the satisfaction equation: • Sample selection • Omitted variables • Reverse causality • Measurement error

35. ASSOCIATION VS. CAUSALITY ANALYSIS It is not possible to adress these identification problems in this study. Because • The LSS data have limited information (e.g. No geographic codes). • Absence of economic and social shifters in Turkey.

36. ASSOCIATION VS. CAUSALITY ANALYSIS Thus, the association analysis is performed in this study: It aims to: • Investigate the presence of relationship between informal employment and satisfaction measures. • Determine the direction of this relationship. • Evaluate the strengths of this relationship in absolute and relative terms.

37. SATISFACTION MEASURES BY INFORMALITY STATUS

38. SATISFACTION MEASURES BY INFORMALITY STATUS

39. MAIN ESTIMATION RESULTS

40. MAKING SENSE OF ESTIMATED COEFFICIENTS

41. MAKING SENSE OF ESTIMATED COEFFICIENTS Compensating variation: The additional amount of money the person need to compensate exactly for any bad occurence in life. • It indicates the magnitude of extra income to equalize the satisfaction level of an informal worker with that of a formal worker. • Can be considered as a measure of (un)pleasentness of the event of interest.

42. MAKING SENSE OF ESTIMATED COEFFICIENTS

43. MAKING SENSE OF ESTIMATED COEFFICIENTS

44. MAKING SENSE OF ESTIMATED COEFFICIENTS

45. MAIN ESTIMATION RESULTS

46. MAIN ESTIMATION RESULTS

47. ESTIMATION RESULTS BY GENDER

48. ESTIMATION RESULTS BY GENDER

49. ESTIMATION RESULTS BY AGE

50. ESTIMATION RESULTS BY AGE