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Onur Ery i lmaz N esli Uz Nazım Karagöz

Agglomeration Economies in Japan: Technical Efficiency, Growth and Unemployment by Arup Mitra & Hajime Sato. Onur Ery i lmaz N esli Uz Nazım Karagöz Turan Atakan Aktay Bilal Mercan. The aim of the study. Regional Diversity T able 1.

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Onur Ery i lmaz N esli Uz Nazım Karagöz

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  1. Agglomeration Economies in Japan: Technical Efficiency, Growth and Unemploymentby Arup Mitra &Hajime Sato Onur Eryilmaz Nesli Uz Nazım Karagöz Turan Atakan Aktay Bilal Mercan

  2. The aim of the study

  3. Regional DiversityTable 1

  4. Strong correlation between employment and gross value added shares (0.84) • Strongcorrelation between capital and gross value added shares (0.93) • Correlation between employment and capital shares is relatively small (0.77).

  5. The correlation between unemployment and growth is - 0.30 • The correlation between the proportion of total manufacturing employment to total workforce and the unemployment rate is around −0.58. • The percentage share of manufacturing employment in the total workforce and per capita income show a reasonable degree of association between them (0.50). • Correlation of population density and per capita income (0.64). (Stronger)

  6. We can say that: • there is a positive relationship between agglomeration and growth, and these factors decrease unemployment.

  7. Methodology • The significance of agglomeration economies and their beneficial effects are examined in two steps. • In the first step, they use the concept of frontier production function, and estimate technical efficiency. • The stochastic frontier production function is defined by Ypi = F(Kpi ,L pi) exp(Vpi − Upi ) • where p & i=prefecture and industry • Y = value added, K=capital, L=labor • U = a non-negative random variable • V = a random error term.

  8. Methodology • In the second step, they examine the association between the technical efficiency and per capita income, unemployment rate and the agglomeration variable. • The agglomeration variable is conceptualized in terms of two alternative indices, namely the proportion of manufacturing employment and population density.

  9. Methodology • Since empirical estimation of such a model requires inclusion of several variables for the equations to be identified, they prefer to base their estimation on factor analysis. • A simple correlation analysis takes only two variables at a time, while factor analysis enables them to observe the association among a group of variables at one time. • The significant factors are identified on the basis of the eigenvalue. If the eigenvalue is greater than one, then the factor is significant.

  10. Empirical Results • For each of the industry groups, Cobb-Douglas production function has been estimated in a stochastic frontier framework. • Both in terms of t-ratios corresponding to the coefficients and the chi-square values representing the overall goodness of fit of the equations, and the results are satisfactory.

  11. Empirical Results • The coefficients of the elasticity of value added with respect to employment and with respect to capital are both positive for all the industries. • The results presented in Table 4 shows that, for most of the industry groups, at least one of the two agglomeration specific variables seems to have a positive association with efficiency.

  12. Empirical Results • Agglomeration effects are relatively stronger in light goods industries (food, textiles, furniture, etc) than heavy industries. • The per capita income also has a positive sign for most of the industry groups. • The agglomeration economies lead to higher economic growth by raising the total factor productivity growth.

  13. Empirical Results • They support the idea that, higher growth also generates employment opportunities and, hence, large urban centers are characterized by lower unemployment rates. • Also they find out the existence of many other mechanisms through which agglomeration economies generate higher growth

  14. İstanbul is a metropolitan city being of a center of production, marketing, substructure, labor and social structure. In İstanbul the population is continuing to increase and that’s why is being attractive for new investments. These investments are effecting next generation and population and resulting in a agglomeration. Moreover, we are not reaching a result such as being a negative factor for the economy.

  15. Till the end of 1980s %52 of KOBİs and %40 of labor are in İstanbul. But there is a problem that İstanbul carries a risk about its natural structure such as earthquakes. Because of this local enterpreneurs should be supported.

  16. Although it is said that there is an decrease in unemployment rate year by year in Turkey generally, in more industrialized cities like İstanbul and Adana there is more unemloyment than the other cities.

  17. It is interesting that the unemloyment rate is higher in the cities which are developed economically than the others.

  18. İstanbul, Adana, İzmir and Bursa are looking for qualified work force and for this reason the unqulified work force is increasing the unemployment rate

  19. For this problem there are some methods which are being tried for solution such as…

  20. CONCLUSION

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