A Cross‐national Comparison of R&D Expenditure Decisions: Tax Incentives and Financial Constraints*

We provide evidence on the impact of tax incentives and financial constraints on corporate R&D expenditure decisions. We contribute to extant research by comparing R&D expenditures in the United States and Canada, thereby exploiting the differences in the two countries' R&D tax credit mechanisms and generally accepted accounting principles. The two tax incentive mechanism designs are consistent with differing views of the degree of financial constraints faced by firms in these economies. Our sample also allows us to explore the effects of capitalizing R&D on Canadian firms. Employing a matched design, we document relations between tax credit incentives and R&D spending consistent with both Canadian and U.S. public companies responding as though they are not financially constrained. We estimate that the Canadian credit system induces, on average, $1.30 of additional R&D spending per dollar of taxes forgone while the U.S. system induces, on average, $2.96 of additional spending. We also find that firms that capitalize R&D costs in Canada spend, on average, 18 percent more on R&D. Collectively, this evidence is important to the ongoing debates in both countries concerning the appropriate design of incentives for R&D and is consistent with the assumptions found in the U.S. tax credit system, but not those found in the Canadian system.     

Dividend Imputation and Shareholder Wealth: The Case of New Zealand

On April 1, 1988, New Zealand stopped the double taxation of dividends by implementing a full dividend imputation program. Because many believed that the tax advantage of debt had led to more highly leveraged firms subject to greater financial risk than was socially optimal, it was hoped the removal of incentives to finance with debt would result in a more efficient allocation of capital. The empirical results suggest that the shareholder wealth gain from dividend imputation was more than offset in firms with large debt levels. Moreover, an examination of debt ratios indicates debt levels declined in the post–imputation period.     

Age-test Markov chains for drug testing and detection

Random urinalysis strategies stratified by time since the last test are characterized with a set of Markov chain models. The probability of a person being tested depends on the amount of time since the person's last test. The Nuclear Regulatory Commission (NRC) has proposed a two strata drug testing strategy based on time since last test. The proposal included a high testing rate for people not yet tested in a given time period and a low testing rate for people testing negative in a given time period. Southern California Edison has implemented a variation of the NRC proposal. These strategies can be modeled within a Markov chain framework. Time to detection is calculated as a function of testing probabilities and drug usage levels. Drug user gaming strategies are discussed with illustrations. These models are implemented as part of a U.S. Navy drug policy analysis system.     

Effects of adjustment of the green drachma to its current exchange rate

Between 1981 and 1988, the drachma has devalued by 62.5% against the ECU. Until mid-1985 any devaluation of the drachma was followed by a corresponding devaluation of the ‘green drachma‘. After that period, the green rate either remained unchanged or changed by a substantially smaller percentage, resulting in farmers' income loss and consumers' gain. The aim of this paper is to investigate the welfare effects on production/producer, consumption/consumer and budgetary flows from and to FEOGA assuming that an adjustment of the green drachma to its current exchange rate was realized. For this purpose partial analysis methodology is employed. The main findings are that, following a simultaneous adjustment of both rates, the gains to producers and in exchange flows more than make up for the corresponding consumers' losses for all products except beef.     

The Nested PIGLOG Model: An Application to U.S. Food Demand

A new demand system is introduced, the Nested PIGLOG model, nesting thirteen other demand systems including five that are also new. This new model and its nested special cases are applied to models of U.S. food demand that include food-at-home (FAH), food-away-from-home (FAFH), and alcoholic beverages. Although nested tests and out-of-sample forecasting performance favor generalizing models to a certain degree, statistically insignificant improvements to in-sample-fit and even poorer out-of-sample forecast accuracy undermine further generalizations. Based on a subset of preferred models, FAFH is found to be price and income elastic compared to FAH which is price and income inelastic.     

Modeling Conditional Yield Densities

Given the increasing interest in agricultural risk, many have sought improved methods to characterize conditional crop-yield densities. While most have postulated the Beta as a flexible alternative to the Normal, others have chosen nonparametric methods. Unfortunately, yield data tends not to be sufficiently abundant to invalidate many reasonable parametric models. This is problematic because conclusions from economic analyses, which require estimated conditional yield densities, tend not to be invariant to the modeling assumption. We propose a semiparametric estimator that, because of its theoretical properties and our simulation results, enables one to empirically proceed with a higher degree of confidence.