Wendy E. Dunn

Unemployment Expectations, Jumping (S,S) Triggers, and Household Balance Sheets

This paper examines the relationship between household balance sheets, consumer purchases, and expectations. We find few robust empirical relationships between balance sheet measures and spending, but we do find that unemployment expectations are robustly correlated with spending. We then construct a formal model of durables and nondurables consumption with an explicit role for unemployment and for household debt. We find that the model is capable of explaining several empirical regularities which are, at best, unexplained by standard models. Finally, we show that a loosening of liquidity constraints can produce a runup in debt similar to that experienced recently in the United States, and that after such a liberalization consumer purchases show heightened sensitivity to labor income uncertainty, providing a potential rigorous interpretation of the widespread view that the buildup of debt in the 1980s may have played an important role in the weakness of consumption during and after the 1990 recession.

How Fast do Personal Computers Depreciate? Concepts and New Estimates

This paper provides new estimates of depreciation rates for personal computers using an extensive database of prices of used PCs. Our results show that PCs lose roughly half their remaining value, on average, with each additional year of use. We decompose that decline into age-related depreciation and a revaluation effect, where the latter effect is driven by the steep ongoing drop in the constant-quality prices of newly-introduced PCs. Our results are directly applicable for measuring the depreciation of PCs in the National Income and Product Accounts (NIPAs) and were incorporated into the December 2003 comprehensive NIPA revision. Regarding tax policy, our estimates suggest that the current tax depreciation schedule for PCs closely tracks the actual loss of value in a zero-inflation environment. However, because the tax code is not indexed for inflation, the tax allowances would be too small in present value for inflation rates above the very low level now prevailing.

Incentives and Prices for Motor Vehicles: What Has Been Happening in Recent Years?

We address the construction of price indexes for consumer vehicles using data collected from a national sample of dealerships. The dataset contains highly disaggregate data on actual sales prices and quantities, along with information on customer cash rebates, financing terms, and much more. Using these data, we are able to capture the actual cash and financing incentives taken by consumers, and we demonstrate that their inclusion in measures of consumer vehicle prices is important. We also document other features of retail vehicle markets that interact and overlap with price measurement issues. In particular, we construct vehicle price indexes under different assumptions about what constitutes a new product in moving from one model year to the next. For the period that we study (1999 to 2003), a period during which incentives became more widespread and new model introductions rose, our preferred price index drops faster than the CPI for new vehicles.

How Fast Do Personal Computers Depreciate? Concepts and New Estimates

This paper provides new estimates of depreciation rates for personal computers (PCs) using an extensive database on prices of used PCs. Our results show that PCs lose roughly half their remaining value, on average, with each additional year of use. We decompose that decline into age-related depreciation and a revaluation effect driven by the steep ongoing drop in the constant-quality prices of newly introduced PCs. Our results are directly applicable for measuring the depreciation of PCs in the National Income and Product Accounts (NIPAs) and were incorporated into the December 2003 comprehensive NIPA revision. Regarding tax policy, our estimates suggest that the current tax depreciation schedule for PCs closely tracks their actual loss of value in a zero-inflation environment. However, because the tax code is not indexed for inflation, the tax allowances would be too small in present value for inflation rates above the very low level now prevailing.

Why are Inventory-Sales Ratios at U.S. Auto Dealerships so High?

Motor vehicle dealerships in the United States tend to hold inventories equivalent to around 65 days’ worth of sales, a relatively high level that has been nearly unchanged for 50 years. Despite playing a prominent role in the volatility of U.S. business cycles, very little is known about why the auto industry targets inventory stocks at such a high level. We use a panel of inventory and sales data from 41 vehicle brands over 30 years and the solutions to two well-known inventory planning problems to show that vehicle inventories appear to be related to (1) the size of dealership franchise networks, which tend to be large; (2) product variety, which tends to be high; and (3) the volatility of new vehicle sales, which also tends to be high. We show that differences across brands in these variables explain a good bit of the cross-section dispersion in brand inventory-sales ratios. Offsetting changes in these factors over time also help explain why the industry’s overall inventory-sales ratio has been quite flat for many decades. More recently, the net increase observed in the inventory-sales ratio in the past couple of years is in contrast to fit of the model, which might suggest that some of that increase could reverse in the coming years.

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.