National Bureau of Economic Research

About: National Bureau of Economic Research is a nonprofit organization based out in Cambridge, Massachusetts, United States. It is known for research contribution in the topics: Monetary policy & Population. The organization has 2626 authors who have published 34177 publications receiving 2818124 citations. The organization is also known as: NBER & The National Bureau of Economic Research.

Do Managerial Objectives Drive Bad Acquisitions

Abstract: This paper documents for a sample of 327 US acquisitions between 1975 and 1987 three forces that systematically reduce the announcement day return of bidding firms. The returns to bidding shareholders are lower when their firm diversifies, when it buys a rapidly growing target , and when the performance of its managers has been poor before the acquisition. These results are consistent with the proposition that managerial rather than shareholders' objectives drive bad acquisitions.

Computing Inequality: Have Computers Changed the Labor Market?

Abstract: This paper examines the effect of technological change and other factors on the relative demand for workers with different education levels and on the recent growth of U.S. educational wage differentials. A simple supply-demand framework is used to interpret changes in the relative quantities, wages, and wage bill shares of workers by education in the aggregate U.S. labor market in each decade since 1940 and over the 1990 to 1995 period. The results suggest that the relative demand for college graduates grew more rapidly on average during the past 25 years (1970-95) than during the previous three decades (1940-70). The increased rate of growth of relative demand for college graduates beginning in the 1970s did not lead to an increase in the college/high school wage differential until the 1980s because the growth in the supply of college graduates increased even more sharply in the 1970s before returning to historical levels in the 1980s. The acceleration in demand shifts for more-skilled workers in the 1970s and 1980s relative to the 1960s is entirely accounted for by an increase in within- industry changes in skill utilization rather than between-industry employment shifts. Industries with large increases in the rate of skill upgrading in the 1970s and 1980s versus the 1960s are those with greater growth in employee computer usage, more computer capital per worker, and larger shares of computer investment as a share of total investment. The results suggest that the spread of computer technology may "explain" as much as 30 to 50 percent of the increase in the rate of growth of the relative demand for more-skilled workers since 1970.

Who Trusts Others

Abstract: Both individual experiences and community characteristics influence how much people trust each other. Using individual level data drawn from US localities we find that the strongest factors associated with low trust are: i) a recent history of traumatic experiences; ii) belonging to a group that historically felt discriminated against, such as minorities (blacks in particular) and, to a lesser extent, women; iii) being economically unsuccessful in terms of income and education; iv) living in a racially mixed community and/or in one with a high degree of income disparity. Religious beliefs and ethnic origins do not significantly affect trust. The role of racial cleavages leading to low trust is confirmed when we explicitly account for individual preferences on inter-racial relationships: within the same community, individuals who express stronger feelings against racial integration trust relatively less the more racially heterogeneous the community is.

Estimating Log Models: To Transform or Not to Transform?

Abstract: Data on health care expenditures, length of stay, utilization of health services, consumption of unhealthy commodities, etc. are typically characterized by: (a) nonnegative outcomes; (b) nontrivial fractions of zero outcomes in the population (and sample); and (c) positively-skewed distributions of the nonzero realizations. Similar data structures are encountered in labor economics as well. This paper provides simulation-based evidence on the finite-sample behavior of two sets of estimators designed to look at the effect of a set of covariates x on the expected outcome, E(y|x), under a range of data problems encountered in every day practice: generalized linear models (GLM), a subset of which can simply be viewed as differentially weighted nonlinear least-squares estimators, and those derived from least-squares estimators for the ln(y). We consider the first- and second- order behavior of these candidate estimators under alternative assumptions on the data generating processes. Our results indicate that the choice of estimator for models of ln(E(x|y)) can have major implications for empirical results if the estimator is not designed to deal with the specific data generating mechanism. Garden-variety statistical problems - skewness, kurtosis, and heteroscedasticity - can lead to an appreciable bias for some estimators or appreciable losses in precision for others.

Estimating Trade Flows: Trading Partners and Trading Volumes

Abstract: We develop a simple model of international trade with heterogeneous firms that is consistent with a number of stylized features of the data. In particular, the model predicts positive as well as zero trade flows across pairs of countries, and it allows the number of exporting firms to vary across destination countries. As a result, the impact of trade frictions on trade flows can be decomposed into the intensive and extensive margins, where the former refers to the trade volume per exporter and the latter refers to the number of exporters. This model yields a generalized gravity equation that accounts for the self-selection of firms into export markets and their impact on trade volumes. We then develop a two-stage estimation procedure that uses an equation for selection into trade partners in the first stage and a trade flow equation in the second. We implement this procedure parametrically, semiparametrically, and nonparametrically, showing that in all three cases the estimated effects of trade frictions are similar. Importantly, our method provides estimates of the intensive and extensive margins of trade. We show that traditional estimates are biased and that most of the bias is due not to selection but rather due to the omission of the extensive margin. Moreover, the effect of the number of exporting firms varies across country pairs according to their characteristics. This variation is large and particularly so for trade between developed and less developed countries and between pairs of less developed countries.