Paul Lengermann

Sectoral Productivity in the United States: Recent Developments and the Role of IT

Abstract This paper introduces new estimates of recent productivity developments in the United States, using an appropriate theoretical framework for aggregating industry multi-factor productivity (MFP) to sectors and the total economy. Our work sheds light on the sources of the continued strong performance of US productivity since 2000.We find that the major sectoral players in the late 1990s pickup were not contributors to the more recent surge in productivity. Rather, striking gains in MFP in the finance and business service sector, a resurgence in MFP growth in the industrial sector, and an end to drops elsewhere more than account for the aggregate acceleration in productivity in recent years. Further, some evidence is found for a link between IT intensity and the recent productivity acceleration.

How Long Do the Benefits of Training Last? Evidence of Long Term Effects Across Current and Previous Employers

This paper uses NLSY data from 1979-1993 to estimate trainings effect on one year wage growth. Year-byyear training histories are constructed which allow the returns to training received at both current and previous employers to vary over time. The time patterns of the returns to training are constructed for both long and short spells of training over nine and three year periods respectively. These returns are then estimated for different demographic groups in order to see how education level, test scores, and occupation influence the payoff to training. Both company training and formal schooling were associated with significant wage growth even nine years after they occurred. Company training was associated with significant wage growth effects irrespective of whether workers changed jobs, although wage growth was higher when the training occurred at a previous employer. Contrary to the conventional human capital model, employers appear to be sharing the costs and returns of general training. While training incidence was lowest for high school dropouts, their return to getting training was the highest. College graduates, in contrast, received the most training but benefited the least. These results suggest an under-supply of training opportunities for low skilled workers.

Offshoring Bias in U.S. Manufacturing: Implications for Productivity and Value Added

The rapid growth of offshoring has sparked a contentious debate over its impact on the U.S. manufacturing sector, which has recorded steep employment declines yet strong output growth--a fact reconciled by the notable gains in manufacturing productivity. We maintain, however, that the dramatic acceleration of imports from developing countries has imparted a significant bias to the official statistics. In particular, the price declines associated with the shift to low-cost foreign suppliers are generally not captured in input cost and import price indexes. Although cost savings are a primary driver of the shift in sourcing to foreign suppliers, the price declines associated with offshoring are not systematically observed; this is the essence of the measurement problem. To gauge the magnitude of these discounts, we draw on a variety of evidence from import price microdata from the Bureau of Labor Statistics, industry case studies, and the business press. To assess the implications of offshoring bias for manufacturing productivity and value added, we implement the bias correction developed by Diewert and Nakamura (2009) to the input price index in a growth accounting framework, using a variety of assumptions about the magnitude of the discounts from offshoring. We find that from 1997 to 2007 average annual multifactor productivity growth in manufacturing was overstated by 0.1 to 0.2 percentage point and real value added growth by 0.2 to 0.5 percentage point. Furthermore, although the bias from offshoring represents a relatively small share of real value added growth in the computer and electronic products industry, it may have accounted for a fifth to a half of the growth in real value added in the rest of manufacturing.

The contribution of multinational corporations to U.S. productivity growth, 1977-2000

In this paper, we decompose aggregate labor productivity growth in order to gauge the relative importance of multinational corporations (MNCs) to the economic performance of the United States in the 1990s. As we define it, the MNC sector refers to the U.S. activities of multinational corporations operating in the United States. We develop productivity estimates for MNCs using (1) published and unpublished industry-level data from two surveys conducted by the Bureau of Economic Analysis and (2) productivity data for industries and major sectors from the FRB productivity system (Bartelsman and Beaulieu 2003, 2004). The resulting MNC sector accounted for about 40 percent of the gross product of all nonfinancial corporations and all of the pickup in nonfinancial corporate labor productivity in the late 1990s. Accordingly, the MNC sector accounted for more than half of the acceleration in labor productivity growth of all U.S. nonfarm private businesses.

High-frequency Spending Responses to the Earned Income Tax Credit

Many households face large, high-frequency changes in income and have limited financial buffers to smooth their consumption through this income volatility. However, few studies have quantified spending responses to such timing shifts in income due to a lack of high-frequency spending data. We use a new dataset of anonymized daily, state-level spending to study a two-week delay in federal tax refunds with an earned income tax credit (EITC) in 2017.

The Effect of Hurricane Matthew on Consumer Spending

Severe weather events, such as blizzards and hurricanes, can temporarily disrupt economic activity. The imprints of these events on aggregate statistics can make it challenging for macroeconomists to analyze and forecast economic conditions. As one illustration, the minutes from March FOMC meetings in six of the past seven years cited unseasonable temperatures or winter storms as influencing economic activity. Weather events present an opportunity to observe how consumers adjust their spending in the face of unanticipated shocks. Thus far, however, there has been little analysis of the spending effects from weather events, partly due to a lack of data at both a sufficiently high frequency and a geographically detailed level. For example, official statistics, such as retail sales from the Census Bureau, are only estimated nationally at a monthly frequency. In this note, we take a step forward in this regard using a new dataset of transaction volumes to examine how consumers reacted to Hurricane Matthew, which struck the East Coast in October 2016. Our results reveal that the hurricane significantly reduced consumer spending in the affected states (Florida, Georgia, South Carolina, and North Carolina) in early October. Although the level of spending after the storm quickly returned to normal, very little of the preceding shortfall appears to have been made up in the subsequent weeks, suggesting that, on net over the span of a few weeks, the hurricane had a negative effect on spending. The drop in activity was most apparent in the discretionary components of spending, such as restaurants, as opposed to necessities, such as grocery stores.2 The net negative effect on spending implies that inter-temporal smoothing through this temporary shock is either incomplete or slow to occur.

The Effect of Sales-Tax Holidays on Consumer Spending

Over the past decade, many U.S. states have enacted policies that temporarily exempt consumer purchases of certain goods from state sales taxes. In this note, we investigate whether the pre-announced sales-tax holidays noticeably alter the spending behavior of consumers. Specifically, we investigate whether there are shifts in the level and/or composition of consumer spending before, during, and after these sales-tax holidays.

Another Look at Residual Seasonality in GDP

According to the Bureau of Economic Analysis, real GDP rose at an annual rate of 1.2 percent in the first quarter of this year, a step down from the 2.3 percent pace in the second half of last year. However, we argue in this note that residual seasonality is unlikely to be the primary reason for the slowdown in first-quarter growth this year.