In the household sector of the Flow of Funds Accounts, the difference between net acquisition of financial assets and net financial savings is equal to a statistical discrepancy which is often quite large relative to the reported changes in asset holdings. This means that the budget restrictions...

Count data regressions are an important tool for empirical analyses ranging from analyses of patent counts to measures of health and unemployment. Along with negative binomial, Poisson panel regressions are a preferred method of analysis because the Poisson conditional fixed effects maximum...

We look into the impact of measurement error in capital on the estimation of production functions. We introduce an identification scheme and an estimation procedure that jointly deals with measurement error in capital and the standard simultaneity bias due to unobserved productivity shocks. We...

Weights are found for weighted least squares estimates such that a selected coefficient (a) changes by one standard deviation or (b) changes in sign. The length of the vector of weight changes is equal to the usual OLS standard error divided by the White-corrected standard errors. Thus the...

The estimator holding the central place in the theory of the multivariate "errors-in-the-variables" (EV) model results from performing orthogonal recession on variables rescaled according to the covariance matrix of the errors [7]. Our first principal finding, via Monte Carlo on the univariate...

Most Difference-in-Difference (DD) papers rely on many years of data and focus on serially correlated outcomes. Yet almost all these papers ignore the bias in the estimated standard errors that serial correlation introduce4s. This is especially troubling because the independent variable of...

In both corporate finance and asset pricing empirical work, researchers are often confronted with panel data. In these data sets, the residuals may be correlated across firms and across time, and OLS standard errors can be biased. Historically, the two literatures have used different solutions...

To estimate causal effects from observational data, an applied researcher must impose beliefs. The instrumental variables exclusion restriction, for example, represents the belief that the instrument has no direct effect on the outcome of interest. Yet beliefs about instrument validity do not...

In this paper we show that omitted variables and publication bias lead to severely biased estimates of the value of a statistical life. Although our empirical results are obtained in the context of a study of choices about road safety, we suspect that the same issues plague the estimation of...

We measure and examine data error in health, education and income statistics used to construct the Human Development Index. We identify three sources of data error which are due to (i) data updating, (ii) formula revisions and (iii) thresholds to classify a country's development status. We...