Estimating elasticities with frontier and other regressions in evaluating two advertising strategies for US Army recruiting

To help resolve a long-standing debate in the US Government on advertising strategies for military recruitment, this study applies ordinary least squares (OLS), which here includes (1) stochastic frontier analysis (SFA) and (2) frontierized least squares (FLS), to evaluate two distinct advertising strategies: Service Specific vs. Joint. Thus, in contrast to the customary use of a single central tendency method, such as OLS, on different models, we here use multiple methods on a single model to cross check and validate results. In addition to serving as cross checks, the methods can be used to identify classic problems, including biases in the data and shortcomings in one or more of the methodologies employed. To avoid dealing with problems on identifying motives underlying various patterns in advertising expenditure, data are drawn from a statistically designed experiment where the expenditures were controlled as part of the experiment to resolve the issue of a choice between the two advertising strategies of interest. In contrast to earlier studies, the current paper finds that all methods used lead to the same conclusion: Service Specific is more efficient than Joint, at least for the US Army—which is, by far, the largest military advertiser. Finally, the paper introduces a new method for reallocating advertising budgets between the Uniformed Services which (a) is simpler than the customary use of cross partial derivatives, (b) avoids the need for the ceteris paribus assumptions for each such allocation, as in customary reallocation methods and (c) simplifies matters so that, for instance, it is not necessary to introduce an entirely new organization to administer the desired coordinating activities.     

On the distribution of city sizes

The city size distribution in many countries is remarkably well described by a Pareto distribution. We derive conditions that standard urban models must satisfy in order to explain this regularity. We show that under general conditions urban models must have (i) a balanced growth path and (ii) a Pareto distribution for the underlying source of randomness. In particular, one of the following combinations can induce a Pareto distribution of city sizes: (i) preferences for different goods follow reflected random walks, and the elasticity of substitution between goods is 1; or (ii) total factor productivities of different goods follow reflected random walks, and increasing returns are equal across goods.     

Measuring Financial Contagion Using Time‐Aligned Data: The Importance of the Speed of Transmission of Shocks*

This paper presents a new empirical approach to address the problem of trading time differences between markets in studies of financial contagion. In contrast to end‐of‐business‐day data common to most contagion studies, we employ price observations, which are exactly aligned in time to correct for time‐zone and end‐of‐business‐day differences between markets. Additionally, we allow for time lags between price observations in order to test the assumption that the shock is not immediately transmitted from one market to the other. Our analysis of the financial turmoil surrounding the Asian crisis reveals that such corrections have an important bearing on the evidence for contagion, independent of the methodology employed. Using a correlation‐based test, we find more contagion the faster we assume the shock to be transmitted.     

Cross-country variation in household access to financial services

This paper presents estimates, for more than 160 countries, of the fraction of the adult population using formal financial intermediaries. The estimates are constructed by combining information on account numbers at banks and microfinance institutions (together with banking depth and GDP data) with estimates from household surveys for a smaller set of countries. An illustrative application of the data compares them with information on poverty: there is a correlation, but it is not clearly causal.     

Portfolio selection subject to experts' judgments

Since Markowitz [Markowitz, H. M. (1952). Portfolio selection. The Journal of Finance, 7, 77-91.], mean-variance theory has assumed that risky-asset returns to be random variables. The theory deals with this uncertainty by further assuming that investors hold homogeneous beliefs regarding the probability distribution governing return uncertainty. While the theory deals with return uncertainty, it fails to address measurement imprecision. In his original work, Markowitz recognized the need to combine randomness with heterogeneous expert judgment resulting in such imprecision. The main objective contributions of the paper are (i) to explore the implications of fuzzy return indeterminacy on mean-variance optimal portfolio choice, (ii) to use bid-ask spread as a proxy measure of the indeterminacy or “fuzzy” nature of random returns, and (iii) to introduce a brief, self-contained glimpse of empirical representations to practitioners unfamiliar with the fuzzy modeling field. Exposition, such as this one, is expected to open new collaborations between other branches of fuzzy mathematics and asset-pricing theories.     

Het quotiënt van Von Neumann bij regressie-analyse

Some remarks are made concerning the application of the VON NEUMANN ratio in testing the residuals of a regression against serial correlation.
Special attention is paid to the fact that in general the VON NEUMANN ratio increases when first differences of the original variables are used.     

A note on linear utility

This note shows how a spectrum of specific axiomatizations for linear utility for decision-making under risk can be integrated under a generalized axiom scheme in which one of the two binary relations used in the axioms parameterizes specific applications.     

A NOTE ON SEMIPARAMETRIC ESTIMATION OF FINITE MIXTURES OF DISCRETE CHOICE MODELS WITH APPLICATION TO GAME THEORETIC MODELS*

We view a game abstractly as a semiparametric mixture distribution and study the semiparametric efficiency bound of this model. Our results suggest that a key issue for inference is the number of equilibria compared to the number of outcomes. If the number of equilibria is sufficiently large compared to the number of outcomes, root‐n consistent estimation of the model will not be possible. We also provide a simple estimator in the case when the efficiency bound is strictly above zero.     

Is there a role for uncertainty in forecasting output growth in OECD countries? Evidence from a time-varying parameter-panel vector autoregressive model

This paper uses a time-varying parameter-panel vector autoregressive (TVP-PVAR) model to analyze the role played by domestic and US news-based measures of uncertainty in forecasting the growth of industrial production of 12 Organisation for Economic Co-operation and Development (OECD) countries. Based on a monthly out-of-sample period of 2009:06 to 2017:05, given an in-sample of 2003:03 to 2009:05, there are only 46% of cases where domestic uncertainty can improve the forecast of output growth relative to a baseline monetary TVP-PVAR model, which includes inflation, interest rate and nominal exchange rate growth, besides output growth. Moreover, including US uncertainty does not necessarily improve the forecasting performance of output growth from the TVP-PVAR model which includes only the domestic uncertainty along with the baseline variables. So, in general, while uncertainty is important in predicting the future path of output growth in the 12 advanced economies considered, a forecaster can do better in majority of the instances by just considering the information from standard macroeconomic variables.