Search results

This chapter uses new data sets to analyze labor market integration between 1882 and 1936 in an area of Asia stretching from South India to Southeastern China and encompassing the three Southeast Asian countries of Burma, Malaya, and Thailand. We find that by the late nineteenth century, globalization, of which a principal feature was the mass migration of Indians and Chinese to Southeast Asia, gave rise to both an integrated Asian labor market and a period of real wage convergence. Integration did not, however, extend beyond Asia to include core industrial countries. Asian and core areas, in contrast to globally integrated commodity markets, showed divergent trends in unskilled real wages.

Research in Economic History, Volume 25, includes six chapters covering a range of geographic areas and tackling a range of issues in economic history. The first two address United States topics, one analyzing data from the eighteenth and the other from the twentieth century. Both have a macroeconomic focus. Peter Mancall, Josh Rosenbloom, and Tom Weiss consider growth in colonial America, while Gary Richardson examines the role of bank failures in propagating the Great Depression.

This paper compares alternative estimation procedures for multi-level factor models which imply blocks of zero restrictions on the associated matrix of factor loadings. We suggest a sequential least squares algorithm for minimizing the total sum of squared residuals and a two-step approach based on canonical correlations that are much simpler and faster than Bayesian approaches previously employed in the literature. An additional advantage is that our approaches can be used to estimate more complex multi-level factor structures where the number of levels is greater than two. Monte Carlo simulations suggest that the estimators perform well in typical sample sizes encountered in the factor analysis of macroeconomic data sets. We apply the methodologies to study international comovements of business and financial cycles.

The purpose of this paper is to investigate whether the macroeconomic effects of government spending shocks vary with the degree of macroeconomic uncertainty.

The authors use quarterly US data from 1960 to 2017 and employ the Self-Exciting Interacted VAR (SEIVAR) to compute nonlinear generalized impulse response functions (GIRFs) to an orthogonalized government spending shock during tranquil and in uncertain times. The parsimonious design of the SEIVAR enables us to focus on extreme deciles of the uncertainty distribution and to control for the financing side of the government budget, monetary policy, financial frictions and consumer confidence.

Fiscal spending has positive output effects in tranquil times, but is contractionary during times of heightened macroeconomic uncertainty. The results indicate an important role of the endogenous response of macroeconomic uncertainty. Investigating different government spending purposes, only increases in research and development expenditures reduce uncertainty and boost output during uncertain times.

The authors contribute to the literature in using a method which allows to control for a large set of confounding factors and accounts for the uncertainty response.