Identification and the Liquidity Effect of a Monetary Policy Shock

Conventional wisdom holds that unanticipated expansionary monetary policy shocks cause transient but persistent decreases in real and nominal interest rates. However a number of econometric studies argue that the evidence favors the opposite view, namely that these shocks actually raise, rather than lower, short term interest rates. We show that this conclusion is not robust to the measure of monetary aggregate used or to the assumptions made to identify monetary policy disturbances. For example, when our analysis is done using non borrowed reserves, we find strong evidence in favor of the conventional view. Existing challenges to the conventional view lack credibility not just because of their fragility. They are based upon measures of policy disturbances which generate seemingly implausible implications about things other than interest rates.

Is Theory Really Ahead of Measurement? Current Real Business Cycle Theories and Aggregate Labor Market Fluctuations

In the l93Os, Dunlop and Tarshis observed that the correlation between hours and wages is close to zero. This classic observation has become a litmus test by which macroeconomic models are judged. Existing real business cycle models fail this test dramatically. Based on this result, we argue that technology shocks cannot be the sole impulse driving post-war U.S. business cycles. We modify prototypical real business cycle models by allowing government spending shocks to influence labor market dynamics in a way suggested by Aschauer (1985), Barro (1981, 1987) and Kormendi (1983), This modification can, in principle, bring the models into closer conformity with the data. While the empirical performance of the models is significantly improved, they still fail to account for the Dunlop-Tarshis observation. Accounting for that observation will require further advances in model development. Consequently, we conclude that theory is behind, not ahead of, business cycle measurement.

Temporal Aggregation and Structural Inference in Macroeconomics

This paper examines the quantitative importance of temporal aggregation bias in distorting parameter estimates and hypothesis tests. Our strategy is to consider two empirical examples in which temporal aggregation bias has the potential to account for results which are widely viewed as being anomalous from the perspective of particular economic models. Our first example investigates the possibility that temporal aggregation bias can lead to spurious Granger causality relationships. The quantitative importance of this possibility is examined in the context of Granger causal relations between the growth rates of money and various measures of aggregate output. Our second example investigates the possibility that temporal aggregation bias can account for the slow speeds of adjustment typically obtained with stock adjustment models. The quantitative importance of this possibility is examined in the context of a particular class of continuous and discrete time equilibriurn models of inventories and sales. The different models are compared on the basis of the behavioral implications of the estimated values of the structural parameters which we obtain and their overall statistical performance. The empirical results from both examples provide support for the view that temporal aggregation bias can be quantitatively important in the sense of Significantly distorting inference.

What Happens After a Technology Shock?

We provide empirical evidence that a positive shock to technology drives per capita hours worked, consumption, investment, average productivity and output up. This evidence contrasts sharply with the results reported in a large and growing literature that argues, on the basis of aggregate data, that per capita hours worked fall after a positive technology shock. We argue that the difference in results primarily reflects specification error in the way that the literature models the low-frequency component of hours worked.

The Effects of Monetary Policy Shocks: Some Evidence from the Flow of Funds

This paper uses the Flow of Funds accounts to assess the impact of a monetary policy shock on the borrowing and lending activities of different sectors of the economy. Our measures of contractionary monetary policy shocks have the following properties: (i) they are associated with a fall in nonborrowed reserves, total reserves, M1, the Federal Reserves' holdings of government securities and a rise in the federal funds rate, (ii) they lead to persistent declines in real GNP, employment, retail sales and nonfinancial corporate profits as well as increases in unemployment and manufacturing inventories, (iii) they generate sharp, persistent declines in commodity prices and (iv) the GDP price deflator does not respond to them for roughly a year. After that the GDP price deflator declines. Our major findings regarding the borrowing activities of different sectors can be summarized as follows. First, following a contractionary shock to monetary policy, net funds raised by the business sector increases for roughly a year. Thereafter, as the recession induced by the policy shock gains momentum, net funds raised by the business sector begins to fall. This pattern is not captured by existing monetary business cycle models. Second, we cannot reject the view that households do not adjust their financial assets and liabilities for several quarters after a monetary shock. This is consistent with a key assumption of several recent monetary business cycle models.

Nominal rigidities and the dynamic effects of a shock to monetary policy

The authors’ model, embodying moderate amounts of nominal rigidities, accounts for the observed inertia in inflation and persistence in output. The key features of their model are those that prevent a sharp rise in marginal costs after an expansionary shock to monetary policy. Of these features, the most important are staggered wage contracts of average duration (three quarters) and variable capital utilization.Inflation (Finance) ; Monetary policy ; Wages

The Response of Hours to a Technology Shock: Evidence Based on Direct Measures of Technology

We investigate what happens to hours worked after a positive shock to technology, using the aggregate technology series computed in Basu, Fernald and Kimball (1999). We conclude that hours worked rise after such a shock.

Online Appendix to "Firm-Specific Capital, Nominal Rigidities and the Business Cycle"

Online appendix for the Review of Economic Dynamics article

Firm-Specific Capital, Nominal Rigidities and the Business Cycle

Macroeconomic and microeconomic data paint conflicting pictures of price behavior. Macroeconomic data suggest that inflation is inertial. Microeconomic data indicate that firms change prices frequently. We formulate and estimate a model which resolves this apparent micro - macro conflict. Our model is consistent with post-war U.S. evidence on inflation inertia even though firms re-optimize prices on average once every 1.5 quarters. The key feature of our model is that capital is firm-specific and pre-determined within a period.