A Parsimonious Macroeconomic Model for Asset Pricing

I study asset prices in a two‐agent macroeconomic model with two key features: limited stock market participation and heterogeneity in the elasticity of intertemporal substitution in consumption (EIS). The model is consistent with some prominent features of asset prices, such as a high equity premium, relatively smooth interest rates, procyclical stock prices, and countercyclical variation in the equity premium, its volatility, and in the Sharpe ratio. In this model, the risk‐free asset market plays a central role by allowing non‐stockholders (with low EIS) to smooth the fluctuations in their labor income. This process concentrates non‐stockholders' labor income risk among a small group of stockholders, who then demand a high premium for bearing the aggregate equity risk. Furthermore, this mechanism is consistent with the very small share of aggregate wealth held by non‐stockholders in the U.S. data, which has proved problematic for previous models with limited participation. I show that this large wealth inequality is also important for the model's ability to generate a countercyclical equity premium. When it comes to business cycle performance, the model's progress has been more limited: consumption is still too volatile compared to the data, whereas investment is still too smooth. These are important areas for potential improvement in this framework.     

Complements or Substitutes? Culture–Technology Interactions in Healthcare

The U.S. government recommends that hospitals adopt Computerized Provider Order Entry (CPOE) systems to improve the quality problems that plague U.S. hospitals. However, CPOE studies show mixed results. We hypothesize that CPOE effectiveness depends on the prevalence of patient safety culture within a hospital. Using organizational information processing theory, we describe how patient safety culture and CPOE enable healthcare organizations to better process information. Specifically, we posit that CPOE complements some aspects of patient safety culture and substitutes for others. Using ridge regression, we empirically test this proposition using data from 268 hospitals and multiple data sources. Results show that while CPOE complements the patient safety dimensions of handoffs and transitions, feedback and communication about error, and organizational learning, CPOE substitutes for the dimension of management support for safety, in the context of our dependent variable. As organizations work to implement new systems, this research can help decision‐makers understand how culture impacts such initiatives and account for culture when anticipating effects.     

Explaining Investment Dynamics in U.S. Manufacturing: A Generalized (S,s) Approach

In this paper we derive a model of aggregate investment that builds from the lumpy microeconomic behavior of firms facing stochastic fixed adjustment costs. Instead of the standard sharp (S,s) bands, firms' adjustment policies take the form of a probability of adjustment (adjustment hazard) that responds smoothly to changes in firms' capacity gap. The model has appealing aggregation properties, and yields nonlinear aggregate time series processes. The passivity of normal times is, occasionally, more than offset by the brisk response to large accumulated shocks. Using within and out-of-sample criteria, we find that the model performs substantially better than the standard linear models of investment for postwar sectoral U.S. manufacturing equipment and structures investment data.     

The state of the art— long range economic and manpower forecasting

This paper discusses the present state of the art in long range economic and manpower forecasting. The problem of comprehensive long range forecasting is viewed as one of integrating classical econometric forecasting models with detailed interindustry and manpower models. Major attention is given here to the problem of output conversion— translating aggregate econometric forecasts into industry detail—and the manner in which this is accomplished in the major U.S. forecasting models. Problems involved in projecting input-output coefficients and labor productivity are analyzed and some serious deficiencies in U.S. occupational data are identified.     

Residential Mortgages and Public Policy: What to do with Fannie and Freddie?

The current debate on U.S. housing policy focuses on the role of the government in supporting the mortgage market. Existing organizations (Fannie Mae/Freddie Mac) are in conservatorship status, and Congress is considering alternative structures and guarantees including the Johnson‐Crapo bill, to provide catastrophic insurance in support of the coverage from private companies. The resolution of this issue is complicated by the various activities involved in the issue—investment securities, public policy, macroeconomics, accounting, and insurance. This article reviews the impact of these activities on U.S. housing, with a discussion of the feasibility of creating a catastrophic insurance program similar to that of the Federal Deposit Insurance Corporation. The federal government has successfully operated catastrophic insurance programs in support of private sector initiatives, and this experience—while certainly not perfect—may be a reasonable approach to the current Fannie/Freddie dilemma.     

Uncertainty Shocks in a Model of Effective Demand

Can increased uncertainty about the future cause a contraction in output and its components? An identified uncertainty shock in the data causes significant declines in output, consumption, investment, and hours worked. Standard general‐equilibrium models with flexible prices cannot reproduce this comovement. However, uncertainty shocks can easily generate comovement with countercyclical markups through sticky prices. Monetary policy plays a key role in offsetting the negative impact of uncertainty shocks during normal times. Higher uncertainty has even more negative effects if monetary policy can no longer perform its usual stabilizing function because of the zero lower bound. We calibrate our uncertainty shock process using fluctuations in implied stock market volatility, and show that the model with nominal price rigidity is consistent with empirical evidence from a structural vector autoregression. We argue that increased uncertainty about the future likely played a role in worsening the Great Recession. The economic mechanism we identify applies to a large set of shocks that change expectations of the future without changing current fundamentals.     

End‐of‐Sample Instability Tests

This paper considers tests for structural instability of short duration, such as at the end of the sample. The key feature of the testing problem is that the number, m, of observations in the period of potential change is relatively small—possibly as small as one. The well‐known F test of Chow (1960) for this problem only applies in a linear regression model with normally distributed iid errors and strictly exogenous regressors, even when the total number of observations, n+m, is large. We generalize the F test to cover regression models with much more general error processes, regressors that are not strictly exogenous, and estimation by instrumental variables as well as least squares. In addition, we extend the F test to nonlinear models estimated by generalized method of moments and maximum likelihood. Asymptotic critical values that are valid as n→∞ with m fixed are provided using a subsampling‐like method. The results apply quite generally to processes that are strictly stationary and ergodic under the null hypothesis of no structural instability.     

Strategic Cognition of Operations Executives

The nature of operations executives’ strategic cognition, as the antecedent to their choices about operations strategy, remains underexplored in the literature. This mixed‐methods study examines executives’ thinking about supply chain strategy through the lens of managerial cognition. Our qualitative study at a pharmaceutical distributor, which examined 25 executives’ outlook on the future of the turbulent U.S. healthcare sector and their suggestions for adapting the company's supply chain strategy to that future, suggests that an executive's strategic cognition can be defined by its regulatory focus—whether the executive envisions the future environment in terms of opportunities or threats—and the level of optimism in regards to the envisioned future. We propose a typology that predicts the strategic choices of operations executives based on four types of cognition: pioneering, pushing, protective, and provocative. It describes whether an executive's strategic choices target traditional or novel sources of revenue, and if they seek to influence either the firm's structure and practices or its environment. Our empirical test of the typology using quantitative data collected in a survey of senior operations executives supports the study's propositions associating three of the four types of cognition with their respective preferred strategic choices.     

Mobility and the Return to Education: Testing a Roy Model with Multiple Markets

Self–selected migration presents one potential explanation for why observed returns to a college education in local labor markets vary widely even though U.S. workers are highly mobile. To assess the impact of self–selection on estimated returns, this paper first develops a Roy model of mobility and earnings where workers choose in which of the 50 states (plus the District of Columbia) to live and work. Available estimation methods are either infeasible for a selection model with so many alternatives or place potentially severe restrictions on earnings and the selection process. This paper develops an alternative econometric methodology that combines Lee's (1983) parametric maximum order statistic approach to reduce the dimensionality of the error terms with more recent work on semiparametric estimation of selection models (e.g., Ahn and Powell (1993)). The resulting semiparametric correction is easy to implement and can be adapted to a variety of other polychotomous choice problems. The empirical work, which uses 1990 U.S. Census data, confirms the role of comparative advantage in mobility decisions. The results suggest that self–selection of higher educated individuals to states with higher returns to education generally leads to upward biases in OLS estimates of the returns to education in state–specific labor markets. While the estimated returns to a college education are significantly biased, correcting for the bias does not narrow the range of returns across states. Consistent with the finding that the corrected return to a college education differs across the U.S., the relative state–to–state migration flows of college– versus high school–educated individuals respond strongly to differences in the return to education and amenities across states.     

Some Limitations of “Risk = Threat × Vulnerability × Consequence” for Risk Analysis of Terrorist Attacks

Several important risk analysis methods now used in setting priorities for protecting U.S. infrastructures against terrorist attacks are based on the formula: Risk=Threat×Vulnerability×Consequence. This article identifies potential limitations in such methods that can undermine their ability to guide resource allocations to effectively optimize risk reductions. After considering specific examples for the Risk Analysis and Management for Critical Asset Protection (RAMCAP?) framework used by the Department of Homeland Security, we address more fundamental limitations of the product formula. These include its failure to adjust for correlations among its components, nonadditivity of risks estimated using the formula, inability to use risk‐scoring results to optimally allocate defensive resources, and intrinsic subjectivity and ambiguity of Threat, Vulnerability, and Consequence numbers. Trying to directly assess probabilities for the actions of intelligent antagonists instead of modeling how they adaptively pursue their goals in light of available information and experience can produce ambiguous or mistaken risk estimates. Recent work demonstrates that two‐level (or few‐level) hierarchical optimization models can provide a useful alternative to Risk=Threat×Vulnerability×Consequence scoring rules, and also to probabilistic risk assessment (PRA) techniques that ignore rational planning and adaptation. In such two‐level optimization models, defender predicts attacker's best response to defender's own actions, and then chooses his or her own actions taking into account these best responses. Such models appear valuable as practical approaches to antiterrorism risk analysis.     

Multicriteria Preference Disaggregation for Classification Problems with an Application to Global Investing Risk*

Mathematical programming and multicriteria approaches to classification and discrimination are reviewed, with an emphasis on preference disaggregation. The latter include the UTADIS family and a new method, Multigroup Hierarchical DIScrimination (MHDIS). They are used to assess investing risk in 51 countries that have stock exchanges, according to 27 criteria. These criteria include quantitative and qualitative measures of market risk (volatility and currency fluctuations); range of investment opportunities; quantity and quality on market information; investor protection (security regulations treatment of minority shareholders); and administrative “headaches” (custody, settlement, and taxes). The model parameters are determined so that the results best match the risk level assigned to those countries by experienced international investment managers commissioned by The Wall Street Journal. Among the six evaluation models developed, one (MHDIS) classifies correctly all countries into the appropriate groups. Thus, this model is able to reproduce consistently the evaluation of the expert investment analysts. The most significant criteria and their weights for assessing global risk investing are also presented, along with their marginal utilities, leading to identifiers of risk groups and global utilities portraying the strength of each country's risk classification. The same method, MHDIS, outperformed the other five methods in a 10‐fold validation experiment. These results are promising for the study of emerging new markets in fast‐growing regions, which present fertile areas for investment growth but also     

Solving the Feldstein–Horioka Puzzle With Financial Frictions

Unlike the prediction of a frictionless open economy model, long‐term average savings and investment rates are highly correlated across countries—a puzzle first identified by Feldstein and Horioka (1980). We quantitatively investigate the impact of two types of financial frictions on this correlation. One is limited enforcement, where contracts are enforced by the threat of default penalties. The other is limited spanning, where the only asset available is noncontingent bonds. We find that the calibrated model with both frictions produces a savings–investment correlation and a volume of capital flows close to the data. To solve the puzzle, the limited enforcement friction needs low default penalties under which capital flows are much lower than those in the data, and the limited spanning friction needs to exogenously restrict capital flows to the observed level. When combined, the two frictions interact to endogenously restrict capital flows and thereby solve the Feldstein–Horioka puzzle.     

Constants and Variants in Political Exchange

ABSTRACT: The purpose of this article is to offer some clarification on developments in a number of European countries in the postwar period. The crux of the analysis are the relations between the huge, functional interest-group organizations and the political system and government, and in particular the trade unions. The intent is firstly to overcome the uncertain and often indistinct use of the concepts of political exchange and corporatism, then to offer an explanatory framework in which these modes, which have prevailed in Capitalist countries, can be grouped under the model of political exchange, in so much as the trade unions’representation of interest groups is affected by the factors and political advantages at stake. It then clariries the essential connotations of this model, which can be considered as constants compared to the variants within it, and also deals with the two types of political exchange predominant in the period and countries surveyed, namely pluralist and cor-poratist variants. Finally the author stresses the need for empirical studies in postwar Europe, to check the acceptability and realism of the model used and test the validity of the theses here outlined, that is, that there are several variants — or strategies — of political exchange between trade unions and the governments and political system.     

Capital‐skill Complementarity and Inequality: A Macroeconomic Analysis

The supply and price of skilled labor relative to unskilled labor have changed dramatically over the postwar period. The relative quantity of skilled labor has increased substantially, and the skill premium, which is the wage of skilled labor relative to that of unskilled labor, has grown significantly since 1980. Many studies have found that accounting for the increase in the skill premium on the basis of observable variables is difficult and have concluded implicitly that latent skill‐biased technological change must be the main factor responsible. This paper examines that view systematically. We develop a framework that provides a simple, explicit economic mechanism for understanding skill‐biased technological change in terms of observable variables, and we use the framework to evaluate the fraction of variation in the skill premium that can be accounted for by changes in observed factor quantities. We find that with capital‐skill complementarity, changes in observed inputs alone can account for most of the variations in the skill premium over the last 30 years.     

An Enforceable Indoor Air Quality Standard for Environmental Tobacco Smoke in the Workplace1

Environmental tobacco smoke (ETS)has recently been determined by U.S. environmental and occupational health authorities to be a human carcinogen. We develop a model which permits using atmospheric nicotine measurements to estimate nonsmokers’ETS lung cancer risks in individual workplaces for the first time. We estimate that during the 1980s, the U.S. nonsmoking adult population's median nicotine lung exposure (homes and workplaces combined)was 143 micrograms (μg)of nicotine daily, and that most-exposed adult nonsmokers inhaled 1430 μg/day. These exposure estimates are validated by pharmacokinetic modeling which yields the corresponding steady-state dose of the nicotine metabolite, cotinine. For U.S. adult nonsmokers of working age, we estimate median cotinine values of about 1.0 nanogram per milliliter (ng/ml)in plasma, and 6.2 ng/ml in urine; for most-exposed nonsmokers, we estimate cotinine concentrations of about 10 ng/ml in plasma and 62 ng/ml in urine. These values are consistent to within 15% of the cotinine values observed in contemporaneous clinical epidemiological studies. Corresponding median risk from ETS exposure in U.S. nonsmokers during the 1980s is estimated at about two lung cancer deaths (LCDs)per 1000 at risk, and for most-exposed nonsmokers, about two LCDs per 100. Risks abroad appear similar. Modeling of the lung cancer mortality risk from passive smoking suggests that de minimis [i.e., “acceptable” (10^-6)], risk occurs at an 8-hr time-weighted-average exposure concentration of 7.5 nanograms of ETS nicotine per cubic meter of workplace air for a working lifetime of 40 years. This model is based upon a linear exposure-response relationship validated by physical, clinical, and epidemiological data. From available data, it appears that workplaces without effective smoking policies considerably exceed this de minimis risk standard. For a substantial fraction of the 59 million nonsmoking workers in the U.S., current workplace exposure to ETS also appears to pose risks exceeding the de manifestos risk level above which carcinogens are strictly regulated by the federal government.     

Multi-item inventory model with quantity-dependent inventory costs and demand-dependent unit cost under imprecise objective and restrictions: A geometric programming approach

A multi-item inventory model with constant demand and infinite replenishment is developed under the restrictions on storage area, total average shortage cost and total average inventory investment cost. These restrictions may be precise or imprecise. Here, it is assumed that inventory costs are directly proportional to the respective quantities, and unit purchase/production cost is inversely related to the demand. Restricted shortages are allowed but fully backlogged. First, the problem is formulated in crisp environment taking the deterministic and precise inventory parameters. It is solved by both geometric programming (GP) and gradient-based non-linear programming (NLP) methods. Later, the problem is formulated with fuzzy goals on constraints and objectives where impreciseness is introduced through linear membership functions. It is solved using the fuzzy geometric programming (FGP) method. The inventory models are illustrated with numerical values and compared with the crisp results. A sensitivity analysis on the optimum order quantity and average cost is also presented due to the variation in the tolerance of total average inventory investment cost and total average shortage cost following Dutta et al., 1993, Fuzzy Sets and Systems, 55, 133-142.     

Beauty and the Labor Market: Accounting for the Additional Effects of Personality and Grooming

This paper examines the influence of three non‐cognitive personal traits — beauty, personality, and grooming — on the labor market earnings of young adults. It extends the analyses of Hamermesh and Biddle [1994 , American Economic Review 84(5): 1174–1194] and others who focus primarily on the effects of beauty on labor market earnings. We find that personality and grooming significantly affect wages, and their inclusion in a model of wage determination reduces somewhat the effects of beauty. We also find some evidence of employer discrimination based on these traits in the setting of wages.     

New Data,Strategies, and Insights for Listeria monocytogenes Dose‐Response Models: Summary of an Interagency Workshop, 2011

Listeria monocytogenes is a leading cause of hospitalization, fetal loss, and death due to foodborne illnesses in the United States. A quantitative assessment of the relative risk of listeriosis associated with the consumption of 23 selected categories of ready‐to‐eat foods, published by the U.S. Department of Health and Human Services and the U.S. Department of Agriculture in 2003, has been instrumental in identifying the food products and practices that pose the greatest listeriosis risk and has guided the evaluation of potential intervention strategies. Dose‐response models, which quantify the relationship between an exposure dose and the probability of adverse health outcomes, were essential components of the risk assessment. However, because of data gaps and limitations in the available data and modeling approaches, considerable uncertainty existed. Since publication of the risk assessment, new data have become available for modeling L. monocytogenes dose‐response. At the same time, recent advances in the understanding of L. monocytogenes pathophysiology and strain diversity have warranted a critical reevaluation of the published dose‐response models. To discuss strategies for modeling L. monocytogenes dose‐response, the Interagency Risk Assessment Consortium (IRAC) and the Joint Institute for Food Safety and Applied Nutrition (JIFSAN) held a scientific workshop in 2011 (details available at http://foodrisk.org/irac/events/ ). The main findings of the workshop and the most current and relevant data identified during the workshop are summarized and presented in the context of L. monocytogenes dose‐response. This article also discusses new insights on dose‐response modeling for L. monocytogenes and research opportunities to meet future needs.     

Benchmarking multilevel methods in leadership: The articles,the model,and the data set

Multilevel data-analytic techniques are rarely simultaneously employed and directly contrasted with each other. In this special issue of The Leadership Quarterly, hierarchical linear models (HLM), within-and-between analysis (WABA), and random group resampling (RGR) are compared and contrasted by testing the hypothesis that leadership moderates the relationship between stressors and well-being—a hypothesis that has important practical implications for the U.S. Army. This first article plays the groundwork for subsequent comparisons by testing for moderating effects using data collected from 2042 U.S. Army soldiers deployed to Haiti in November and December of 1994. Raw-score or individual-level analyses failed to find evidence of moderating effects. However, a preliminary set of group-level analyses indicated that the data had significant group-level properties that had not been modeled in the individual-level analyses. The group-level properties of the data set the stage for the three multilevel data-analytic approaches (HLM, WABA, and RGR) that are employed in three articles that follow and that are then compared and contrasted in the final article of this special issue.     

Priority Rules and Other Asymmetric Rationing Methods

In a rationing problem, each agent demands a quantity of a certain commodity and the available resources fall short of total demand. A rationing method solves this problem at every level of resources and individual demands. We impose three axioms: Consistency—with respect to variations of the set of agents—Upper Composition and Lower Composition—with respect to variations of the available resources. In the model where the commodity comes in indivisible units, the three axioms characterize the family of priority rules, where individual demands are met lexicographically according to an exogeneous ordering of the agents. In the (more familiar) model where the commodity is divisible, these three axioms plus Scale Invariance—independence of the measurement unit—characterize a rich family of methods. It contains exactly three symmetric methods, giving equal shares to equal demands: these are the familiar proportional, uniform gains, and uniform losses methods. The asymmetric methods in the family partition the agents into priority classes; within each class, they use either the proportional method or a weighted version of the uniform gains or uniform losses methods.