Knowledge that Transforms

JEL No. J20,L25,L53 We use a new database, the National Establishment Time Series (NETS), to revisit the debate about the role of small businesses in job creation. Birch (e.g., 1987) argued that small firms are the most important source of job creation in the U.S. economy, but Davis et al. (1996a) argued that this conclusion was flawed, and based on improved methods and using data for the manufacturing sector they concluded that there was no relationship between establishment size and net job creation. Using the NETS data, we examine evidence for the overall economy, as well as for different sectors. The results indicate that small establishments and small firms create more jobs, on net, although the difference is much smaller than what is suggested by Birch's methods. However, the negative relationship between establishment size and job creation is much less clear for the manufacturing sector, which may explain some of the

We identify employees at seven companies whose 401(k) investment choices are dominated because they are contributing less than the employer matching contribution threshold despite being vested in their match and being able to make penalty-free 401(k) withdrawals for any reason because they are older than 59½. At the average firm, 36% of match-eligible employees over 59½ forego arbitrage profits that average 1.6% of their annual pay, or $507. A survey educating employees about the free lunch they are foregoing raised contribution rates by a statistically insignificant 0.67 percent of income among those completing the survey.

This paper conducts an event study of the impact of multilateral debt relief initiatives announcements on the stock prices of South African companies with subsidiaries in countries benefited by these initiatives. It shows that these prices increase significantly above those of other firms, especially around the launching of the Multilateral Debt Relief Initiative. These price increases are consistent with lower expected levels of future taxation in the benefited countries and provide evidence of the economic consequences of multilateral debt relief that is robust to reverse causality between economic performance and the decision to grant debt relief.

This paper exploits India's rapid, comprehensive, and externally imposed trade reform to establish a causal link between changes in tariffs and firm productivity. Pro-competitive forces, resulting from lower tariffs on final goods, as well as access to better inputs, due to lower input tariffs, both appear to have increased firm-level productivity, with input tariffs having a larger impact. The effect was strongest in import-competing industries and industries not subject to excessive domestic regulation. While we find no evidence of a differential impact according to state-level characteristics, we observe complementarities between trade liberalization and additional industrial policy reforms.

It is well known that augmenting a standard linear regression model with variables that are correlated with the error term but uncorrelated with the original regressors will increase the asymptotic efficiency of the original coefficients. We argue that in the context of predicting excess returns, valid augmenting variables exist and are likely to yield substantial gains in estimation efficiency and, hence, predictive accuracy. The proposed augmenting variables are ex post measures of an unforecastable component of excess returns: ex post errors from macroeconomic survey forecasts, the surprise components of asset price movements around macroeconomic news announcements, or even the weather. These “surprises” cannot be used directly in forecasting—they are not observed at the time that the forecast is made—but can nonetheless improve forecasting accuracy by reducing parameter estimation uncertainty. We derive formal results about the benefits and limits of this approach and apply it to standard examples of forecasting excess bond and equity returns. We find substantial improvements in out-of-sample forecast accuracy for standard excess bond return regressions; gains for forecasting excess stock returns are much smaller.

Using a proprietary data set of credit bureau records, Cohen-Cole (2011) finds evidence that lenders are using the racial composition of a borrower's neighborhood to set credit limits on revolving accounts. Using the same credit bureau data, I revisit this work and reach two main findings. First, an undocumented decision in constructing the variables appears to have introduced a distortion that is highly correlated with neighborhood racial composition and appears to increase the size of the reported disparity. Second, when neighborhood income is controlled for, the results presented as evidence of redlining disappear.

It is shown that in a nonparametric nonseparable triangular system, the conditional moment restriction (CMR) does not identify the average structural function (ASF). The CMR identifies the ASF only if the model is structurally separable in observable covariates and unobservable random errors. This excludes, for instance, random coefficient models in which the CMR in general does not identify the average response. An implication of our results is that empirical researchers should use methods other than CMR if they want to estimate the average response in models that are not additively separable.

We consider a dynamic stochastic general equilibrium model (DSGE) in which firms follow one of four price‐setting regimes: sticky prices, sticky information, rule of thumb, or full‐information flexible prices. The parameters of the model, including the fraction of each type of firm, are estimated by matching the moments of the observed variables of the model to those found in the data. We find that sticky price firms and sticky information firms jointly account for over 80% of firms in the model. We compare the performance of our hybrid model to pure sticky price and sticky information models along various dimensions, including monetary policy implications.

Most studies of comparative productivities fail to find evidence of convergence in OECD manufacturing despite major economic growth theories predicting convergence. Using manufacturing data for nineteen OECD countries over the period from 1870 to 2006, this study finds strong evidence of unconditional β-convergence as well as σ-convergence. Panel data estimates suggest that the convergence has been driven by domestic R&D, international R&D spillovers, and financial development as predicted by Schumpeterian growth theories.