Knowledge that Transforms

May 01 1999 Rejoinder Michael F. Bryan, Michael F. Bryan Search for other works by this author on: This Site Google Scholar Stephen G. Cecchetti Stephen G. Cecchetti Search for other works by this author on: This Site Google Scholar Author and Article Information Michael F. Bryan Stephen G. Cecchetti Received: December 16 1998 Accepted: December 18 1998 Online ISSN: 1530-9142 Print ISSN: 0034-6535 © 1999 President and Fellows of Harvard College and the Massachusetts Institute of Technology1999 The Review of Economics and Statistics (1999) 81 (2): 203–204. https://doi.org/10.1162/003465399558175 Article history Received: December 16 1998 Accepted: December 18 1998 Cite Icon Cite Permissions Share Icon Share Facebook Twitter LinkedIn Email Views Icon Views Article contents Figures & tables Video Audio Supplementary Data Peer Review Search Site Citation Michael F. Bryan, Stephen G. Cecchetti; Rejoinder. The Review of Economics and Statistics 1999; 81 (2): 203–204. doi: https://doi.org/10.1162/003465399558175 Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll JournalsThe Review of Economics and Statistics Search Advanced Search This content is only available as a PDF. © 1999 President and Fellows of Harvard College and the Massachusetts Institute of Technology1999 Article PDF first page preview Close Modal You do not currently have access to this content.

This paper examines the mobility of individuals through the wage and earnings distributions, using 1979-1991 data from the National Longitudinal Survey of Youth. Lifetime wages will be more equally distributed than wages from any single year if individuals change position in the wage distribution over time. The results suggest that mobility is predominantly within group mobility, reducing wage inequality by 12%-26% over a four-year horizon. A detailed examination of within-group mobility, using year-to-year estimates of transition probabilities among quintiles of the distribution, reveals similar general patterns across all skill groups: mobility declined significantly over the years, especially at the lower end of the wage and earnings distributions.

This paper reconsiders the empirical evidence connecting inflation to its higher-order moments. In particular, we examine the statistical properties of the observed positive correlation between the sample mean and the sample cross-sectional skewness of price changes. This correlation has attracted substantial attention over the years and has recently been the focal point of a debate among macroeconomists. We show that the sample mean-skewness correlation suffers from a small-sample bias that accounts for the entirety of the observed correlation. In other words, we establish that one of the stylized facts in the literature on aggregate price behavior need not be a fact at all.

Nonlinear modeling has become popular in applied macroeconomics. Successful attempts include Beaudry and Koop's CDR (current depth of the recession) model of real GNP, and various STAR (smooth transition autoregression) models of industrial production. However, these models have not been directly compared. We compare CDR and STAR models of U.S. real GNP and industrial production. We find (i) within sample, the CDR model fits slightly better than the STAR model; (ii) out of sample, the CDR model forecasts better than the STAR model; and (iii) the CDR model generates very different dynamics than the STAR model.

This paper reexamines the evidence relating core inflation to cross-sectional inflation asymmetry using statistical measures that are robust to the criticism of Bryan and Cecchetti. The results here suggest that there does exist significant positive correlation between core inflation and cross-sectional inflation asymmetry, but only at the monthly frequency. Furthermore, a sampling problem is highlighted which underscores the importance of careful Monte Carlo analysis when exact small-sample distributions are unknown.

This study investigates the dispersion of price levels within highly disaggregated markets by examining plant-level product records from the U.S. Census of Manufactures. The paper estimates the effects of inflation on price dispersion through cross-sectional variation in the drift rate of average input costs within a market, arguing that, in several models that relate inflation to price dispersion, the effects of cost increases on dispersion is similar to the effects of general inflation. We also disentangle the effects of aggregate and idiosyncratic shocks on price dispersion. In general, we find that the higher the drift rate of input costs of a given commodity, the larger the amount of price dispersion. The standard deviation of idiosyncratic shocks also is positively correlated with the degree of price dispersion.

Traditional analyses of the income tax greatly underestimate deadweight losses by ignoring its effect on forms of compensation and patterns of consumption. The full deadweight loss is easily calculated using the compensated elasticity of taxable income to changes in tax rates because leisure, excludable income, and deductible consumption are a Hicksian composite good. Microeconomic estimates imply a deadweight loss of as much as 30% of revenue or more than ten times Harberger's classic 1964 estimate. The relative deadweight loss caused by increasing existing tax rates is substantially greater and may exceed $2 per $1 of revenue.

We use household-level data covering a ten-year period (1984 to 1993) to investigate the likely determinants of the Italian recession of 1993, the first year after WWII when private consumption fell. Consumption fell most for working-age households and for the self-employed. Our evidence is consistent with the response to permanent negative shocks due to the major pension reform of 1992 and the introduction of stricter tax-compliance measures for the self-employed. This is still true when we control for the role played by job losses and the collapse of the retail sector that characterized the early 1990s.

© 1999 by the President and Fellows of Harvard College and the Massachusetts Institute of Technology

Previous property tax capitalization studies assume that families itemize, that they save in taxable assets, and that real interest income is taxed. However, many families do not itemize, many families invest in tax-deferred assets, and nominal interest income is taxed. As a consequence, prior studies likely misspecify the property tax capitalization equation for roughly ninety percent of their samples. Taking federal tax provisions into account increases the precision of our estimated capitalization rate. In addition, our results suggest that biases in prior studies likely contribute to the variety of capitalization estimates in the literature.