1. North American Summer Meeting Econometric Society
Heterogeneities and Uncertainty in Labor Markets of Developing Countries
María Elisa Farías
North American Summer Meeting Econometric Society
Boston University
June, 2009

2. Index
Motivation
Contribution
The Model
Results
Conclusions

3. Motivation Exogenous shocks are continuously destroying job positions.
Large heterogeneities in labor markets of mature economies and developing countries.
Are there differences in the adjustment capacity to shocks between developing countries and mature economies? How do heterogeneities affect adjustment?
Two adjustment mechanisms in mature economies: wages and unemployment levels. Wage adjustment would be closer to the case of the U.S. economy, where real wages have decreased and wage variance have increased the last years.
The second mechanism would be closer to the case of Continental Europe, specially for less skilled workers.
Do the effects of heterogeneities change with development level?
Higher unemployment rates in Asia and Latin America than the OECD countries during the 1990s. In same cases, as Chile and India, high unemployment remains after growth recovering ( Chile 7%, India 10%, between 1990 and 2004). Lower labor productivity also and large informal labor.

4. What does the theory say?

5. Contribution
Real business cycle model with frictions and heterogeneities in labor markets. Based on Jovanovic (1979), Merz (1995), Mortensen and Pissarides (1999), Pissarides (2000), Den Haan et al. (2000), Yashiv (2000), Acemoglu (2001a), and Albrecht and Vroman (2002), Den Haan et al. (2005), Shimer (2005).
Frictions appear when there are informational problems and
workers look for jobs – search
firms want to hire workers – matching
Frictions are deepened when workers and firms are heterogeneous.
Mismatch problems can arise if the endowments of the human capital of workers do not meet the skill requirements of firms.
Calibrating the model for Chile and Peru (developing countries), I find that frictions and mismatch can explain until 77 percent of the excess of turnover observed in these labor markets, with respect to the U.S. labor market.

6. The Model: Assumptions
Small economy populated by a continuous of heterogeneous workers, indexed along [0,1].
At any time t, workers possess a skill level xte in (0,1]. Workers are member of households.
Standard choice of time devoted to the labor market normalized at unity. Unemployment includes non participation.
Large number of heterogeneous entrepreneurs, differentiated by abilities xtf in (0,1]. Each entrepreneur is a firm.
At any date t, an exogenous shock l appears, destroying job positions, with 0 < l < 1 (Poisson).
Firms create vacancies at a rate v and U unemployed workers search for jobs.
Tightness of the labor market:

7. Households and Firms 1) Households preferences are represented by
0 < b < 1, UC > 0, UCC < 0, UN < 0 and UNN > 0 and the utility function follows
2) Firms combine the entrepreneur skill with the worker skills to produce:
0<m<1
3) Matching: Firms and unemployed workers meet randomly according to
V vacancies of type xf and (1-N) unemployed workers of type xe. Workers search vacant jobs at a rate s.

8. Production Process y M xe f(xe, N0) y = uN0 xf xe u u x Matchingu u x
Matching
Production

9. Central Planner Problem
The central planner solves:
Max W(Wt) = max{V,s}t= {0,inf.}{ U(Ct,Nt) + bE0[W(Wt+1)/Wt ]}
st.
Ct = Yt – b(st)(1 – Nt) – aVt
Nt+1 = (1 – lt)Nt + Mt, < l < 1
xet+1 = xet (1 + g – d) < g < , 0 < d < 1
xft+1 = xft (1 + g – d) g constant
Wt = {Nt,nt, xet,xft} l Markov
The First Order Conditions:
P1)
P2)
with:

10. Competitive Equilibrium - Households
Max Vh(Ft) = max{s}t= (0,inf.){ U(ct,nt) + bE0[W(Ft+1)/Ft ]}
st.
ct + b(st)(1 – nt) = wtnt
nt+1 = nt(1 – lt) + pst(1 – nt) pt = Mt/st(1-Nt)
Nt+1 = (1 – lt)Nt + Mt, 0 < l < 1, 0 < d < 1
xet+1 = xet(1 + g – d) g technical change
wt = w(Ft)
Ft={nt, Nt, xet}
The household Euler equation:

11. Competitive Equilibrium - Firms
Max VF(Gt) = max{v}t= (0,inf.){ f(xft, xetnt) + bE0[VF(Gt+1)/Gt ]}
st.
nt+1 = nt(1 – lt) + qtvt, with qt = Mt/Vt
Nt+1 = (1 – lt)Nt + Mt, with 0 < lt < 1.
xet+1 = xet(1 + g – a)
xft+1 = xft(1 + g – a)
wt = w(Gt) Gt={nt, Nt, xet, xft }.
The firm Euler equation:
There is a Nash equilibrium where wages satisfy:

12. xet+1=(1 + gt - d)xet-1 gt = rgt-1 + et
Calibration
Some Extensions:
Exogenous shocks in the rate of technical change g
xet+1=(1 + gt - d)xet-1 gt = rgt-1 + et
Destruction of human capital from the side of workers (skill destruction)
xet+1=[1 + gt(1-lt)- d]xet-1
Skill-biased matching function (skill bias j)
Mtsb = (jVt)1-g(st(1-Nt))g 0 < j 1

13. Results with constant and variable g

14. Results – Skill Destruction

15. Results – Constant g
Figure 1 – Employment, Output, and Consumption Paths

16. Results - Variable g and skill bias
Figure 2 – Employment, Output, and Consumption Paths

17. Gamma Distributions

18. Conclusions
Main contribution: mismatch between technological requirements and skill endowments would deep frictions in labor markets (specially in emerging countries).
Calibration results show that labor market rigidities and mismatching problems can account for 77 percent of the excess of turnover observed in Chile and Peru, with respect to the US. They can also explain between 50 and 80 percent of the unemployment gaps.
High rates of unemployment, informal labor, and low labor productivity would become structural in these countries due to mismatch, even though a country has reached a medium stage of development.

19. North American Summer Meeting Econometric Society
Heterogeneities and Uncertainty in Labor Markets of Developing Countries
María Elisa Farías
North American Summer Meeting Econometric Society
Boston University
June, 2009

20. Results