This paper explores the effect of discretion in estate valuation techniques on the effective estate tax burden on different asset classes. For some assets, such as liquid securities, there is relatively little discretion in valuation. For other assets, such as partial interests in closely-held businesses, family limited partnerships, and real assets or collectibles that are traded in thin markets, estate valuations may be more difficult to establish. Estate tax filers may therefore be able to select valuations that reduce the reported value of the estate assets, and therefore the effective estate tax burden. In 1998, estates that invoked the doctrine of "minority discounts" in valuing non-controlling interests in limited partnerships claimed an average discount of 36 percent for these assets, relative to their estimated market value. More than half of all limited partnership assets reported on estate tax returns were valued using this doctrine. This suggests that for a given statutory estate tax rate, the effective estate tax burden may be greater on assets that are easily valued than on difficult-tovalue assets. A comparison of the mix of assets reported on estate tax returns, and the mix the estate tax returns would be predicted to hold, given data from the Survey of Consumer Finances, is consistent with lower relative valuations for difficult-to-value assets.

Environmental regulation in the United States has undergone a slow evolution from command and control strategies towards market-based regulations. One such innovation is the Toxics Release Inventory (TRI), a regulation that requires polluting firms to publicly disclose information about their toxic emissions. The basic tenet of this regulation is that it corrects for informational asymmetries between polluters and households, allowing communities to pressure polluters to decrease their emissions. Policy-makers have judged the TRI a tremendous success, as national releases declined by 43% between 1988 and 1999. Yet many of the fundamental problems which are known to lead to the classic failure of the Coase theorem (such as high transaction costs and difficulties in organizing) cast doubt on the effectiveness of disclosure rules, alone, to lead to an efficient outcome in the case of pollution. We use an event study methodology with high-quality data on house prices and other local attributes to assess the extent to which the public values changes in toxic releases and thus the success of TRI. Our major findings include: (1) declines in toxic releases appear unrelated to any political economy variables that might lead to public activism; (2) initial information released under TRI had no significant effect on the distribution of house prices; and (3) house prices show no significant impact of declines in reported toxic releases over time. Standard errors are small enough that we can reject the hypothesis that large declines in toxic releases lead to more than a 0.5% increase in house prices. These results also hold when we control for differences in the availability of information on TRI and the possible effect of expectations. Our findings cast doubt on the ability of the public to process complex information on hazardous emissions and support the Coase theorem in that right-to-know laws such as TRI may not be the most effective form of environmental regulation.

This paper addresses the issue of the optimal trading system for less actively traded (i.e., ‘thinly-traded’) stocks. We compare the performance of a pure order driven market with limit order book (POD) with that of a hybrid order driven market with specialist and limit order book (HOD). We find that the HOD system offers superior performance along several dimensions of market quality. In particular, the specialist-based system offers lower execution costs, greater depth, a significant increase in the depth-to-spread ratio, and lower adverse selection costs. Very ‘thinly-traded’ stocks benefit more than less inactive stocks from the adoption of a hybrid trading system both in terms of greater liquidity and in terms of lower adverse selection costs.

Although forests have diminished globally over the past 400 years, forest cover has increased in some areas, including India in the last two decades. Aggregate time-series evidence on forest growth rates and income growth across countries and within India and a newly assembled data set that combines national household survey data, census data, and satellite images of land use in rural India at the village level over a 29-year period are used to explore the hypothesis that increases in the demand for forest products associated with income and population growth lead to forest growth. The evidence is consistent with this hypothesis, which also shows that neither the expansion of agricultural productivity nor rising wages in India increased local forest cover.

What motivated men to risk death in the most horrific war in U. S. history when pay was low and irregular and military punishment strategies were weak? In such a situation creating group loyalty by promoting social capital is of paramount importance and in the Civil War was the cement of both armies. We find that individual and company socioeconomic and demographic characteristics, ideology, and morale were important predictors of group loyalty in the Union Army. Company characteristics were more important than ideology or morale. Soldiers in companies that were more homogeneous in ethnicity, occupation, and age were less likely to shirk.

Inference methods that recognize the clustering of individual observations have been available for more than 25 years. Brent Moulton (1990) caught the attention of economists when he demonstrated the serious biases that can result in estimating the effects of aggregate explanatory variables on individual-specific response variables. The source of the downward bias in the usual ordinary least-squares (OLS) standard errors is the presence of an unobserved, state-level effect in the error term. More recently, John Pepper (2002) showed how accounting for multi-level clustering can have dramatic effects on t statistics. While adjusting for clustering is much more common than it was 10 years ago, inference methods robust to cluster correlation are not used routinely across all relevant settings. In this paper, I provide an overview of applications of cluster-sample methods, both to cluster samples and to panel data sets.

A Picture Is Worth a Thousand Symbols: A Sociologist's View of the Economic Pursuit of Truth by Joel M. Podolny. Published in volume 93, issue 2, pages 169-174 of American Economic Review, May 2003

Cointegrated bivariate nonstationary time series are considered in a fractional context, without allowance for deterministic trends. Both the observable series and the cointegrating error can be fractional processes. The familiar situation in which the respective integration orders are 1 and 0 is nested, but these values have typically been assumed known. We allow one or more of them to be unknown real values, in which case Robinson and Marinucci (2001, 2003) have justified least squares estimates of the cointegrating vector, as well as narrow-band frequency-domain estimates, which may be less biased. While consistent, these estimates do not always have optimal convergence rates, and they have nonstandard limit distributional behavior. We consider estimates formulated in the frequency domain, that consequently allow for a wide variety of (parametric) autocorrelation in the short memory input series, as well as time-domain estimates based on autoregressive transformation. Both can be interpreted as approximating generalized least squares and Gaussian maximum likelihood estimates. The estimates share the same limiting distribution, having mixed normal asymptotics (yielding Wald test statistics with χ2 null limit distributions), irrespective of whether the integration orders are known or unknown, subject in the latter case to their estimation with adequate rates of convergence. The parameters describing the short memory stationary input series are √n-consistently estimable, but the assumptions imposed on these series are much more general than ones of autoregressive moving average type. A Monte Carlo study of finite-sample performance is included.

We explore the effect of computerization on productivity and output growth using data from 527 large U.S. firms over 1987–1994. We find that computerization makes a contribution to measured productivity and output growth in the short term (using 1-year differences) that is consistent with normal returns to computer investments. However, the productivity and output contributions associated with computerization are up to 5 times greater over long periods (using 5- to 7-year differences). The results suggest that the observed contribution of computerization is accompanied by relatively large and time-consuming investments in complementary inputs, such as organizational capital, that may be omitted in conventional calculations of productivity. The large long-run contribution of computers and their associated complements that we uncover may partially explain the subsequent investment surge in computers in the late 1990s.

This paper empirically tests for a multidimensional separating equilibrium in contract negotiations and tests for evidence of the moral hazard inherent in many contracts. Using contract and performance data on players drafted into the National Football League from 1986 through 1991, we find evidence that players use delay to agreement and incentive clauses to reveal their private information during contract negotiations. In addition, our empirical tests of the moral hazard issue indicate that a player's effort level is influenced by the structure of his contract.