Todd B. Walker

Clearing Up the Fiscal Multiplier Morass

Bayesian prior predictive analysis of five nested DSGE models suggests that model specifications and prior distributions tightly circumscribe the range of possible government spending multipliers. Multipliers are decomposed into wealth and substitution effects, yielding uniform comparisons across models. By constraining the multiplier to tight ranges, model and prior selections bias results, revealing less about fiscal effects in data than about the lenses through which researchers choose to interpret data. When monetary policy actively targets inflation, output multipliers can exceed one, but investment multipliers are likely to be negative. Passive monetary policy produces consistently strong multipliers for output, consumption, and investment.

Government Investment and Fiscal Stimulus in the Short and Long Runs

This paper contributes to the debate about fiscal multipliers by studying the impacts of government investment in conventional neoclassical growth models. The analysis focuses on two dimensions of fiscal policy that are critical for understanding the effects of government investment: implementation delays associated with building public capital projects and expected future fiscal adjustments to debt-financed spending. Implementation delays can produce small or even negative labor and output responses in the short run; anticipated fiscal financing adjustments matter both quantitatively and qualitatively for long-run growth effects. Taken together, these two dimensions have important implications for the short-run and long-run impacts of fiscal stimulus in the form of higher government infrastructure investment. The analysis is conducted in several models with features relevant for studying government spending, including utility-yielding government consumption, time-to-build for private investment, and government production.

Perceptions and Misperceptions of Fiscal Inflation

The Great Recession and worldwide financial crisis have exploded fiscal imbalances and brought fiscal policy and inflation to the forefront of policy concerns. Those concerns will only grow as aging populations increase demands on government expenditures in coming decades. It is widely perceived that fiscal policy is inflationary if and only if it leads the central bank to print new currency to monetize deficits. Monetization can be inflationary. But it is a misperception that this is the only channel for fiscal inflations. Nominal bonds, the predominant form of government debt in advanced economies, derive their value from expected future nominal primary surpluses and money creation; changes in the price level can align the market value of debt to its expected real backing. This introduces a fresh channel, not requiring explicit monetization, through which fiscal deficits directly affect inflation. The paper describes various ways in which fiscal policy can directly affect inflation and explains why these fiscal effects are difficult to detect in time series data.

How Equilibrium Prices Reveal Information in Time Series Models with Disparately Informed, Competitive Traders

Accommodating asymmetric information in a dynamic asset pricing model is technically challenging due to the problems associated with higher-order expectations. That is, rational investors are forced into a situation where they must forecast the forecasts of other agents (i.e., form higher-order expectations). In a dynamic setting, this problem telescopes into the infinite future and the dimension of the relevant state space approaches infinity. By employing the frequency domain approach of Whiteman (1983) and Kasa (2000), this paper demonstrates how information structures previously believed to lead to disparate expectations in equilibrium (e.g., Singleton (1987)) converge to a symmetric equilibrium. The “revealing” aspect of the price process lies in the invertibility of the observed state space, which makes it possible for agents to infer the economically fundamental shocks, thus eliminating the need to forecast the forecasts of others.

Anchoring in Experimental Asset Markets

We investigate the relationship between anchoring and the emergence of bubbles in experimental asset markets. We show that setting a visual anchor at the fundamental value (FV) in the first period only is sufficient to eliminate or to significantly reduce bubbles in laboratory asset markets. If no FV-anchor is set, bubble-crash patterns emerge. Our results indicate that bubbles in laboratory environments are primarily sparked in the first period. If prices are initiated around the FV, they stay close to the FV over the entire trading horizon. Our insights can be related to initial public offerings and the interaction between prices set on pre-opening markets and subsequent intra-day price dynamics.