Agglomeration Economies in Japan: Agglomeration Economies in Japan: Technical Efficiency, Growth and Technical Efficiency, Growth and

UnemploymentUnemploymentby by Arup Mitra &Arup Mitra & Hajime SatoHajime Sato

Onur Eryilmaz Nesli Uz

Nazım Karagöz Turan Atakan Aktay

Bilal Mercan

The aim of the study

Regional Diversity Table 1

Prefecture Employment Gross Value added

Capital

TOKYO % 3.848 %3.856 % 2.796

AICHI % 10.294 % 11.811 % 10.144

• Strong correlation between employment and gross value added shares (0.84)

• Strong correlation between capital and gross value added shares (0.93)

• Correlation between employment and capital shares is relatively small (0.77).

Prefecture Unemployment Rate

Population Density (per km sq)(Agglomeration Variable)

Per capita income

(Growth)

Share of manufacturing employment in total workforce (Agglomeration Variable)

TOKYO %5 5517 4219 14.76

AICHI %4 1366 3481 27.96

• 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)

• We can say that:– there is a positive relationship between

agglomeration and growth, and these factors decrease unemployment.

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.

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.

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.

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.

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.

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.

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

İstanbul is a metropolitan city İstanbul is a metropolitan city being of a center of production, being of a center of production,

marketing, substructure, labor and marketing, substructure, labor and social structure.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.

Till the end of 1980s %52 of Till the end of 1980s %52 of KOBİs and %40 of labor are in KOBİs and %40 of labor are in

İstanbul.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.

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.

It is interesting that the unemloyment rate is higher in the

cities which are developed economically than the others.

İstanbul, Adana, İzmir and Bursa are looking for qualified work force

and for this reason the unqulified work force is increasing the

unemployment rate

For this problem there are some methods which are being tried for

solution such as…

CONCLUSION