Macroeconomic implications of agglomeration

February 22, 2010

By Morris A. Davis, Jonas D. M. Fisher and Toni M. Whited

The authors construct a dynamic general equilibrium model of cities and use it to estimate the effect of local agglomeration on per capita consumption growth. Agglomeration affects growth through the density of economic activity: higher production per unit of land raises local productivity. Firms take productivity as given; produce using a technology that has constant returns in developed land, capital, and labor; and accumulate land and capital. If land prices are rising, as they are empirically, firms economize on land. This behavior increases density and contributes to growth. They use a panel of U.S. cities and our model’s predicted relationship among wages, output prices, housing rents, and labor quality to estimate the net effect of agglomeration on local wages. The impact of agglomeration on the level of wages is estimated to be 2 percent. Combined with their model and observed increases in land prices, this estimate implies that agglomeration raises per capita consumption growth by 10 percent.

This paper fits in a new line of research that tries to understand cities and agglomeration effects using dynamic general equilibrium models. The basis here is the good old Lucas-Prescott island model, the model is used to study the impact of agglomeration on prices (land, labor, goods). Would this explain why Tokyo and New York City are so expensive?


Euler-Equation Estimation for Discrete Choice Models: A Capital Accumulation Application

February 15, 2010

By Russell Cooper, John Haltiwanger and Jonathan Willis

This paper studies capital adjustment at the establishment level. Our goal is to characterize capital adjustment costs, which are important for understanding both the dynamics of aggregate investment and the impact of various policies on capital accumulation. Our estimation strategy searches for parameters that minimize ex post errors in an Euler equation. This strategy is quite common in models for which adjustment occurs in each period. Here, we extend that logic to the estimation of parameters of dynamic optimization problems in which non-convexities lead to extended periods of investment inactivity. In doing so, we create a method to take into account censored observations stemming from intermittent investment. This methodology allows us to take the structural model directly to the data, avoiding time-consuming simulation based methods. To study the effectiveness of this methodology, we first undertake several Monte Carlo exercises using data generated by the structural model. We then estimate capital adjustment costs for U.S. manufacturing establishments in two sectors.

Capital adjustement costs (and often other adjustment costs) are an important ingredient of many business cycle models. Yet, we have very poor estimates of how important they are. Typically, they are calibrated such that some measure of volatility is matched. This paper takes Euler equation estimation seriously and develops a method to estimate from micro data capital adjustment costs, in particular taking into account the irreversability of investment.

A multi-sectoral approach to the U.S. Great Depression

February 8, 2010

By Pedro S. Amaral and James C. MacGee

We document sectoral differences in changes in output, hours worked, prices, and nominal wages in the United States during the Great Depression. We explore whether contractionary monetary shocks combined with different degrees of nominal wage frictions across sectors are consistent with both sectoral as well as aggregate facts. To do so, we construct a two-sector model where goods from each sector are used as intermediates to produce the sectoral goods that in turn produce final output. One sector is assumed to have flexible nominal wages, while nominal wages in the other sector are set using Taylor contracts. We calibrate the model to the U.S. economy in 1929, and then feed in monetary shocks estimated from the data. We find that while the model can qualitatively replicate the key sectoral facts, it can account for less than a third of the decline in aggregate output. This decline in output is roughly half as large as the one implied by a one-sector model. Alternatively, if wages are set using Calvo-type contracts, the decline in output is even smaller.

In recent years, aggregate models have brought interesting answers to light regarding the origin and continuation of the Great Depression, starting with the work of Cole and Ohanian (1999). Cole and Ohanian (2001) extend it to a two sector model with wage rigidities in one sector and show that this contributed little to the Great Depression. Bordo, Erceg and Evans (2000) use a one-sector model with Taylor contracts and find that it can explain a significant part of the Great Depression. Amaral and MacGee combine the two and find only a third of the decline can be explained by these wage rigidities. Is this the end of this debate?

Capital controls and welfare

February 1, 2010

By: Shigeto Kitano

This paper computes welfare levels under different degree of capital controls and compares them with the welfare level under perfect capital mobility by using the methodology of Schmitt-Grohe and Uribe (2007). We show that perfect capital mobility is not always optimal and that capital controls may enhance an economy’s welfare level. There exists an optimal degree of capital-account restriction that achieves a higher level of welfare than that under perfect capital mobility, if the economy has a distortion due to financial intermediaries such as inefficient banks. The results of our analysis imply that as the domestic financial intermediaries are less efficient, the government should impose stricter capital controls in the form of a tax on foreign borrowing.

Would it be beneficial to make markets more incomplete? This would be an example.