Edward S. Knotek

Convenient Prices and Price Rigidity: Cross-Sectional Evidence

This paper provides cross‐sectional evidence of convenient prices—prices that simplify and expedite transactions, reducing the time costs from physically making a transaction. Firms may wish to set convenient prices for items that are typically purchased with cash, are sold alone or with a few similar items, and are high‐traffic transactions, that is, that require queuing or are frequently purchased. I collect a new data set and find broad support for the use of convenient prices in locations where making a rapid transaction is important. Convenience also appears to predominantly affect goods and services with above‐average price rigidity.

Alternative Methods of Solving State-Dependent Pricing Models

We use simulation-based techniques to compare and contrast two methods for solving state-dependent pricing models: discretization, which solves and simulates the model on a grid; and collocation, which relies on Chebyshev polynomials. While both methods produce qualitatively similar results, statistically significant quantitative differences do arise. We present evidence favoring discretization over collocation in this context, given a lack of robustness in the latter.

Nowcasting U.S. Headline and Core Inflation

Forecasting future inflation and nowcasting contemporaneous inflation are difficult. We propose a new and parsimonious model for nowcasting headline and core inflation in the U.S. price index for personal consumption expenditures (PCE) and the consumer price index (CPI). The model relies on relatively few variables and is tested using real-time data. The model’s nowcasting accuracy improves as information accumulates over the course of a month or quarter, and it easily outperforms a variety of statistical benchmarks. In head-to-head comparisons, the model’s nowcasts of CPI inflation outperform those from the Blue Chip consensus, with especially significant outperformance as the quarter goes on. The model’s nowcasts for CPI and PCE inflation also significantly outperform those from the Survey of Professional Forecasters, with similar nowcasting accuracy for core inflation measures. Across all four inflation measures, the model’s nowcasting accuracy is generally comparable to that of the Federal Reserve’s Greenbook.

Drifting inflation targets and monetary stagflation

This paper revisits the phenomenon of stagflation. Using a standard New Keynesian dynamic, stochastic general equilibrium model, we show that stagflation from monetary policy alone is a very common occurrence when the economy is subject to both deviations from the policy rule and a drifting inflation target. Once the inflation target is fixed, the incidence of stagflation in the baseline model is essentially eliminated. In contrast with several other recent papers that have focused on the connection between monetary policy and stagflation, we show that while high uncertainty about monetary policy actions can be conducive to the occurrence of stagflation, imperfect information more generally is not a requisite channel to generate stagflation.

Regime Changes and Monetary Stagflation

This paper examines whether monetary shocks can consistently generate stagflation in a dynamic, stochastic setting. I assume that the monetary authority can induce transitory shocks and longer-lasting monetary regime changes in its operating instrument. Firms cannot distinguish between these shocks and must learn about them using a signal extraction problem. The possibility of changes in the monetary regime greatly improves the ability of money to generate stagflation. This is true whether the regime actually changes or not. If the monetary regime changes on average once every ten years, stagflation occurs in 76% of model simulations. The intuition for this result is simple: increased output volatility due to learning coupled with inflation inertia produce conditions conducive to the emergence of stagflation. The incidence of stagflation can be reduced by a stable, transparent central bank.

Forecasting GDP Growth with NIPA Aggregates

Beyond GDP, which is measured using expenditure data, the U.S. national income and product accounts (NIPAs) provide an income-based measure of the economy (gross domestic income, or GDI), a measure that averages GDP and GDI, and various aggregates that include combinations of GDP components. This paper compiles real-time data on a variety of NIPA aggregates and uses these in simple time-series models to construct out-of-sample forecasts for GDP growth. Over short forecast horizons, NIPA aggregates?particularly consumption and GDP less inventories and trade?together with these simple time-series models have historically generated more accurate forecasts than a canonical AR(2) benchmark. This has been especially true during recessions, although we document modest gains during expansions as well.

Consumer Debt Dynamics: Follow the Increasers

Consumer debt played a central role in creating the U.S. housing bubble, the ensuing housing downturn, and the Great Recession, and it has been blamed as a factor in the weak subsequent recovery as well. This paper uses micro-level data to decompose consumer debt dynamics by separating the actions of consumer debt increasers and decreasers, and then further decomposing movements into percentage and size margins among the increasers and decreasers. We view such a decomposition as informative for macroeconomic models featuring a central role for consumer debt. Using this framework, we show that variations in borrowing activity among the increasers explain four times as much of the total variation in consumer debt as variations among the decreasers who are shedding debt, whether through paydowns or defaults. We also provide micro-level evidence of a sharp decline in the percentage of increasers during the financial crisis that is qualitatively consistent with a binding zero lower bound on nominal interest rates, and evidence of a cycle in the average size of debt changes among the increasers that is related to rising collateral values pre-crisis coupled with additional financial frictions after the crisis.

Drifting Inflation Targets and Stagflation

The 1970s provided the United States its first experience with the phenomenon of stagflation—simultaneously high inflation and poor economic performance in terms of unemployment and GDP. Economists continue to debate the root causes of stagflation. The conventional view is that sharp increases in the price of oil during the decade were to blame: large increases in oil prices raise inflation, which saps purchasing power from consumers and businesses and thus hurts economic activity. But a number of economists also point to a role for monetary policy in generating stagflation, in particular through “go-stop” monetary policy: because inflation tends to move slowly, a period of accommodative monetary policy followed by a sharp tightening of policy can result in stagflation, as output turns down quickly but inflation remains high from the “go” phase. ; This paper examines the ability of monetary policy to generate stagflation. Using a relatively standard macroeconomic model, it shows that stagflation arises regularly in cases where the monetary authority allows its inflation target to move around. If households and firms face great uncertainty about the monetary authority’s inflation target, this scenario is also conducive to the emergence of stagflation—even if the inflation target actually remains unchanged. Thus, the paper finds that limiting monetary policy uncertainty and drift in the inflation target during normal times through clearly communicated, credible, and fixed inflation targets would essentially eliminate the possibility of stagflation from monetary factors.