Scott D. Schuh

Small Business and Job Creation: Dissecting the Myth and Reassessing Thefacts

This paper investigates how job creation and destruction behavior varies by employer size in the U.S. manufacturing sector during the period 1972 to 1988. The paper also evaluates the empirical basis for conventional claims about the job-creating prowess of small businesses. The chief findings and conclusions fall into five categories:(1)Conventional wisdom about the job-creating prowess of small businesses rests on misleading interpretations of the data.(2)Many previous studies of the job creation process rely upon data that are not suitable for drawing inferences about the relationship between employer size and job creation.(3)Large plants and firms account for most newly-created and newly-destroyed manufacturing jobs.(4)Survival rates for new and existing manufacturing jobs increase sharply with employer size.(5)Smaller manufacturing firms and plants exhibit sharply higher gross rates of job creation but not higher net rates.

Monetary Policy, Housing, and Heterogeneous Regional Markets

We quantify the importance of heterogeneity for monetary policy using a new heterogeneous-agent VAR (HAVAR) model that integrates national monetary/financial markets with regional housing markets via the mortgage rate. Although the HAVAR model has linear regional VARs, its aggregate impulse responses exhibit two nonlinearities: (1) time variation, stemming from aggregation over heterogeneous regions, and (2) state dependence on initial economic conditions in regions. Thus, monetary policy has “long and variable lags” because monetary transmission depends on the extent and nature of regional heterogeneity, which both vary over time. The model is estimated with data for U.S. regions from 1986 to 1996 and simulated to show how coastal housing booms might influence the efficacy of monetary policy.

Estimating the linear-quadratic inventory model maximum likelihood versus generalized method of moments

Abstract We compare generalized method of moments (GMM) and maximum likelihood (ML) estimators of the parameters of a linear-quadratic inventory model using nondurable manufacturing data and Monte Carlo simulations. Data-based GMM estimates for five normalizations vary widely, generally rejecting the model. The ML estimate generally supports the model. Monte Carlo experiments reveal that the GMM estimates are often biased (apparently due to poor instruments), statistically insignificant, economically implausible, and dynamically unstable. The ML estimates are generally unbiased (even in misspecified models), statistically significant, economically plausible, and dynamically stable. Asymptotic standard errors for ML are 3 to 15 times smaller than for GMM.

Input and Output Inventories

This paper builds and estimates a new model of firm behavior that includes decisions to order, use and stock input materials in a stage-of-fabrication environment with either gross production or value added technology. The model extends the traditional linear-quadratic model of output (finished goods) inventories by incorporating delivery and usage of input materials plus input inventory investment--features which largely have been ignored in the literature. Stylized facts indicate that input inventories are empirically more important than output inventories, especially in business cycle fluctuations. Firms simultaneously choose input and output inventories; thus, the model exhibits feedback between stocks induced by dynamic stage-of-fabrication linkages. Estimation of inventory decision rules shows the model is reasonably consistent with data in nondurable and durable goods industries. The results reveal inventory stock interaction, convex costs and viability of gross production and value added specifications, industrial differences and input inventory-saving technology.

Input and Output Inventories in General Equilibrium

We build and estimate a two-sector (goods and services) dynamic stochastic general equilibrium model with two types of inventories: materials (input) inventories facilitate the production of finished goods, while finished goods (output) inventories yield utility services. The model is estimated using Bayesian methods. The estimated model replicates the volatility and cyclicality of inventory investment and inventory-to-target ratios. Although inventories are an important element of the models propagation mechanism, shocks to inventory efficiency or management are not an important source of business cycles. When the model is estimated over two subperiods (pre and post 1984), changes in the volatility of inventory shocks or in structural parameters associated with inventories, such as the input inventory to output ratio, play a small role in reducing the volatility of output.

Productivity and U.S. Macroeconomic Performance: Interpreting the Past and Predicting the Future with a Two-Sector Real Business Cycle Model

A two-sector real business cycle model, estimated with postwar U.S. data, identifies shocks to the levels and growth rates of total factor productivity in distinct consumption- and investment-goods-producing technologies. This model attributes most of the productivity slowdown of the 1970s to the consumption-goods sector; it suggests that a slowdown in the investment-goods sector occurred later and was much less persistent. Against this broader backdrop, the model interprets the more recent episode of robust investment and investment-specific technological change during the 1990s largely as a catch-up in levels that is unlikely to persist or be repeated anytime soon.

How consumers pay: adoption and use of payments

Using data from a nationally representative survey on consumer payment behavior, we estimate Heckman two-stage regressions on the adoption and use of seven different payment instruments. We find that the characteristics of payments are important in determining consumer payment behavior, even when controlling for demographic and financial attributes: setup and record keeping are especially important in explaining adoption, while security is important in explaining which methods consumers use for transactions. For the first time, we estimate the number of payment methods adopted by consumers conditional on having access to a bank account, as the unbanked consumers’ payment choices are much more limited than those of consumers with bank accounts. This paper follows the analysis in Schuh and Stavins (2010), but with improved data, allowing us to estimate a better model of payment behavior. As in the previous study, cost is found to significantly affect payment use, indicating that the recent increase in the cost of debit cards issued by some banks may lead to a reduction in U.S. consumers’ reliance on debit cards for transactions.

Explaining Adoption and Use of Payment Instruments by U.S. Consumers

The way that consumers make payments is changing rapidly and attracts important current policy interest. This paper develops and estimates a structural model of adoption and use of payment instruments by U.S. consumers. We use a cross-section of data from the Survey of Consumer Payment Choice, a new survey of consumer behavior. We evaluate substitution and income effects. Our simulations shed light on the consumer response to the 2011 regulation of interchange fees on debit cards imposed by the Dodd-Frank Act, as well as the proposed settlement between Visa and MasterCard and the Department of Justice that would allow merchants to surcharge the use of payment cards.

The Roles of Comovement and Inventory Investment in the Reduction of Output Volatility

Most of the reduction in GDP volatility since the 1983 is accounted for by a decline in comovement of output among industries that hold inventories. This decline is not simply a passive byproduct of reduced volatility in common factors or shocks. Instead, structural changes occurred in the long-run and dynamic relationships among industries’ sales and inventory investment behavior—especially in the automobile and related industries, which are linked by supply and distribution chains featuring new production and inventory management techniques. Using a HAVAR model (Fratantoni and Schuh 2003) with only two sectors, manufacturing and trade, we discover structural changes that reduced comovement of sales and inventory investment both within and between industries. As a result, the response of aggregate output to all types of shocks is dampened. Structural changes accounted for more than 80 percent of the reduction in output volatility, thus weakening the case for “good luck,” and altered industries’ responses to federal funds rate shocks, thus suggesting the case for “better monetary policy” is complicated by changes in the real side of the economy.

Who gains and who loses from credit card payments?: theory and calibrations

Merchant fees and reward programs generate an implicit monetary transfer to credit card users from non-card (or “cash”) users because merchants generally do not set differential prices for card users to recoup the costs of fees and rewards. On average, each cash-using household pays