Neville Francis

A Flexible Finite-Horizon Alternative to Long-Run Restrictions with an Application to Technology Shocks

Recent studies using long-run restrictions question the validity of the technology-driven real business cycle hypothesis. We propose an alternative identification that maximizes the contribution of technology shocks to the forecast-error variance of labor productivity at a long but finite horizon. In small-sample Monte Carlo experiments, our identification outperforms standard long-run restrictions by significantly reducing the bias in the short-run impulse responses and raising their estimation precision. Unlike its long-run restriction counterpart, when our Max Share identification technique is applied to U.S. data, it delivers the robust result that hours worked responds negatively to positive technology shocks.

A Flexible Finite-Horizon Identification of Technology Shocks

Recent empirical studies using in finite horizon long-run restrictions question the validity of the technology-driven real business cycle hypothesis. These results have met with their own controversy, stemming from their sensitivity to changes in model specification and the general poor performance of long-run restrictions in Monte Carlo experiments. We propose an alternative identification that maximizes the contribution of technology shocks to the forecast-error variance of labor productivity at a long, but finite horizon. In small samples, our identification outperforms its in finite horizon counterpart by producing less biased impulse responses and technology shocks that are more highly correlated with the technology shocks from the underlying model. We apply our identification to post-war U.S. data and find that the negative hours response is not robust to allowing a slightly greater role for non-technology shocks in the variance of productivity at long horizons. We conclude that restrictions aimed at isolating the dynamics of productivity beyond business cycle frequencies do not provide information sufficient to robustly predict short-run movements in labor hours.

Monetary Policy in a Markov-Switching Vector Error-Correction Model: Implications for the Cost of Disinflation and the Price Puzzle

Monetary policy vector autoregressions (VARs) typically presume stability of the long-run outcomes. We introduce the possibility of switches in the long-run equilibrium in a cointegrated VAR by allowing both the covariance matrix and weighting matrix in the error-correction term to switch. We find that monetary policy alternates between sustaining long-run growth and disinflationary regimes. Allowing state changes can also help explain the price puzzle and justify the use of commodity prices as a corrective measure. Finally, we show that regime-switching has implications for disinflationary monetary policy and can explain the variety of sacrifice ratio estimates that exist in the literature.

The local effects of monetary policy

Many studies have documented disparities in the regional responses to monetary policy shocks. However, because of computational issues, the literature has often neglected the richest level of disaggregation: the city. In this paper, we estimate the city-level responses to monetary policy shocks in a Bayesian SVAR. The Bayesian SVAR allows us to model the entire panel of metropolitan areas through the imposition of a shrinkage prior. We then seek the origin of the city-level asymmetric responses. We find strong evidence that the population density and the size of the local government sector mitigate the effects of monetary policy on local employment. The roles of the traditional interest rate, equity, and credit channels are marginalized relative to the previous findings based on less-granular definitions of regions. However, the relevance of the interest rate and credit channels appears to be more robust to business cycle uncertainty.

IMPERFECT TRANSMISSION OF TECHNOLOGY SHOCKS AND THE BUSINESS CYCLE CONSEQUENCES

We investigate the business cycle effects of imperfect transmission of technology shocks within a basic real business cycle (RBC) model along two dimensions. First, we assume that agents cannot distinguish a temporary increase in productivity growth from a sustained increase in the underlying growth rate of productivity and instead must conduct signal extraction exercises and update beliefs about the source of aggregated shocks. Second, we propose a technology adjustment cost resulting in the slow diffusion of technological innovations into the production process. Both of these impediments to the transmission of technology result in a large initial wealth effect, increasing investment and hours less, relative to the usual RBC model without these frictions. Furthermore, each of these features is capable of producing a decline in hours on impact of the technology shock matching the negative response in hours found in the data by such works as Gali [American Economic Review 89(1), 249–271 (1999)].

How Has Empirical Monetary Policy Analysis Changed after the Financial Crisis

In the wake of the Great Recession, the Federal Reserve lowered the federal funds rate (FFR) target essentially to zero and resorted to unconventional monetary policy. With the nominal FFR constrained by the zero lower bound (ZLB) for an extended period, empirical monetary models cannot be estimated as usual. In this paper, we consider whether the standard empirical model of monetary policy can be preserved without breaks. We consider whether alternative policy instruments (e.g., a long-term interest rate) can be considered substitutes for the FFR over the ZLB period. Furthermore, we compare the shadow rates proposed in Krippner [2012] and Wu and Xia [2016] as alternative measures of the stance of monetary policy. We ask whether the shadow rate is a sufficient representation of the policy instrument or if the financial crisis requires other modifications. We find that, when using a dataset that spans both the pre-ZLB and ZLB periods, the shadow rate acts as a fairly good proxy for monetary policy by producing impulse responses of macro indicators similar to what we’d expect based on the post-WWII, non-ZLB benchmark and by displaying stable parameter estimates when compared to this benchmark.

Countercyclical Policy and the Speed of Recovery after Recessions

The nature of the business cycle appears to have changed. Prior to the 1990s, recoveries from recessions were quick and steep; after the past three recessions, however, recoveries were weak and prolonged. We consider the effect of a number of countercyclical policies intended to shorten recessions and speed recoveries. Our innovation is to analyze the duration of the recoveries of various U.S. states, which gives us a cross-section of both state- and national-level policies. Because we study multiple recessions for the same state and multiple states for the same recession, we can control for differences in the economic conditions preceding recessions and the causes of the recessions when evaluating various policies. We find that expansionary monetary policy at the national level helps to stimulate the exit of individual states from recession. We also find certain factors extend expected recovery times: other states in the same region suffering from recession around the same time, the length of the preceding recession, and shocks to oil prices at the peak.

Macroeconomic Learning and the Propagation of Technology Shocks

We incorporate learning in a standard dynamic stochastic general equilibrium model along two empirically-supported dimensions. First, we assume that agents cannot directly observe the individual components of the productivity shock and instead must conduct signal extraction exercises and update beliefs about the source of aggregate shocks. For this type of learning to have qualitative impacts on dynamic behavior we must assume either a counterfactually high relative variance or a large persistence parameter on the trend component of productivity. Second, we propose an alternative learning mechanism in which technological innovations diffuse slowly through the economy. This mechanism is successful at generating a variety of empirically observed responses under reasonable parameterizations.