Richard G. Anderson

The role of data/code archives in the future of economic research

This essay examines the role of data and program‐code archives in making economic research ‘replicable.’ Replication of published results is recognized as an essential part of the scientific method. Yet, historically, both the ‘demand for’ and ‘supply of’ replicable results in economics has been minimal. ‘Respect for the scientific method’ is not sufficient to motivate either economists or editors of professional journals to ensure the replicability of published results. We enumerate the costs and benefits of mandatory data and code archives, and argue that the benefits far exceed the costs. Progress has been made since the gloomy assessment of Dewald, Thursby and Anderson some 20 years ago in the American Economic Review, but much remains to be done before empirical economics ceases to be a ‘dismal science’ when judged by the replicability of its published results.

A vector error-correction forecasting model of the US economy

Any research or policy analysis in economics must be consistent with the time-series properties of observed macroeconomic data. Numerous previous studies of such time series reinforce the need to specify correctly a models multivariate stochastic structure. This paper discusses in detail the speciation of a vector error correction forecasting model that is anchored by long-run equilibrium relationships suggested by economic theory. The model includes six variables - the CPI, the implicit price deflator for GDP, real money balances (MI), the federal funds rate, the yield on long-term (10-year) government bonds, and real GDP - and four cointegrating vectors. Model forecasts during the 1990s are compared to those made by the Federal Reserve and by private forecasters.

Nonlinear Relationship Between Permanent and Transitory Components of Monetary Aggregates and the Economy

This paper uses several methods to study the interrelationship among Divisia monetary aggregates, prices, and income, allowing for nonstationary, nonlinearities, asymmetries, and time-varying relationships among the series. We propose a multivariate regime switching unobserved components model to obtain transitory and permanent components for each series, allowing for potential recurrent and structural changes in their dynamics. Each component follows distinct two-state Markov processes representing low or high phases. Since the lead-lag relationship between the phases can vary over time, rather than pre-imposing a structure to their linkages, the proposed flexible framework enables us to study their specific lead-lag relationship over each one of their cycles and over each U.S. recession in the last 40 years. The decomposition of the series into permanent and transitory components reveals striking results. First, we find a strong nonlinear association between the components of money and prices-all low phases of the transitory component of prices were preceded by tight transitory and permanent money phases. We also find that most recessions were preceded by tight money phases (its cyclical and permanent components) and high transitory price phases (with the exception of the 2001 and 2009-2010 recessions). In addition, all recessions were associated with a decrease in transitory and permanent income.

The Perils of Globalization: Offshoring and Economic Insecurity of the American Worker

According to polls from the 2006 congressional elections, globalization and economic insecurity were the primary concerns of many voters. These Americans apparently believe that they have fallen victim to liberal trade polices and that inexorable trends in globalization are destroying the American Dream. In this analysis, we use time series cross-section data from the General Social Survey (GSS) to examine the links among offshoring, labor market volatility, and the demand for social insurance. Unique among the GSS literature, our analysis includes a pseudo-panel model which permits including auxiliary state and regional macroeconomic information.

Mean-Variance vs. Full-Scale Optimization: Broad Evidence for the UK

In the Full-Scale Optimization approach the complete empirical financial return probability distribution is considered; and the utility maximizing solution is found through numerical optimization. Using a portfolio choice setting of three UK equity indices we identify several utility functions featuring loss aversion and prospect theory; under which Full-Scale Optimization is a substantially better approach than the mean-variance approach. As the equity indices have return distributions with small deviations from normality; the findings indicate much broader usefulness of Full-Scale Optimization than has earlier been shown. The results hold in and out of sample; and the performance improvements are given in terms of utility as well as certainty equivalents.

Money and velocity during financial crises: from the Great Depression to the Great Recession

This study models the demand for a broad monetary aggregate (M2) from the Great Depression through the Great Recession. Key to the model is the interaction between a measure of time-variation in economic agents’ perceived financial risk and an index of the cost of portfolio adjustment. The finding of a useful money demand relationship suggests that skepticism regarding the indicator role of a broad, liquid money aggregate as a policy guide may be exaggerated. Further, our model provides some guidance for policymakers who face the challenge of unwinding large balance sheets as risk premia return to normal and velocity adjusts.

The Role of Data & Program Code Archives in the Future of Economic Research

This essay examines the role of data and program-code archives in making economic research replicable. Replication of published results is recognized as an essential part of the scientific method. Yet, historically, both the demand for and supply of replicable results in economics has been minimal. Respect for the scientific method is not sufficient to motivate either economists or editors of professional journals to ensure the replicability of published results. We enumerate the costs and benefits of mandatory data and code archives, and argue that the benefits far exceed the costs. Progress has been made since the gloomy assessment of Dewald, Thursby and Anderson some twenty years ago in the American Economic Review, but much remains to be done before empirical economics ceases to be a dismal science when judged by the replicability of its published results.

Productivity measurement and monetary policymaking during the 1990s

The acceleration of productivity growth during the latter half of the 1990s was both the defining economic event of the decade and a major topic of debate among Federal Reserve policymakers. A key aspect of the debate was the conflict between incoming aggregate data, which initially suggested little productivity gain, and anecdotal firm-level evidence which hinted at an acceleration. Some FOMC members feared an overheating economy and higher inflation; others, including the Chairman, argued that revolutionary increases in productivity were occurring and the Committee should not prematurely forgo significant future gains in real income by tightening policy. We review the difficulty of measuring productivity during periods of rapid quality change, the large magnitude of subsequent data revisions during the 1990s, and, from FOMC transcripts, the contemporary monetary policy debate within the FOMC as the decade*s data evolved.

Analysis of Panel Vector Error Correction Models Using Maximum Likelihood, the Bootstrap, and Canonical-Correlation Estimators

In this paper, we examine the use of Box-Tiao*s (1977) canonical correlation method as an alternative to likelihood-based inferences for vector error-correction models. It is now well-known that testing of cointegration ranks based on Johansen*s (1995) ML-based method suffers from severe small sample size distortions. Furthermore, the distributions of empirical economic and financial time series tend to display fat tails, heteroskedasticity and skewness that are inconsistent with the usual distributional assumptions of likelihood-based approach. The testing statistic based on Box-Tiao*s canonical correlations shows promise as an alternative to Johansen*s ML-based approach for testing of cointegration rank in VECM models.

Does Commonality in Illiquidity Matter to Investors

This paper investigates whether investors are compensated for taking on commonality risk in equity portfolios. A large literature documents the existence and the causes of commonality in illiquidity, but the implications for investors are less understood. In a more than fifty year long sample of NYSE stocks, we find that commonality risk carries a return premium of at least 2.0 per cent annually. The commonality risk premium is statistically and economically significant, and substantially higher than what is found in previous studies. It is robust when controlling for illiquidity level effects, transaction costs, as well as variations in illiquidity measurement.