Using U.S. Consumer Expenditure Surveys, we estimate “quality Engel curves” for 66 durable goods based on the extent richer households pay more for each good. The same data show that the average price paid rises faster from 1980 to 1996 for goods with steeper quality Engel curves, as if households are ascending these curves. BLS prices likewise increase more quickly for goods with steeper quality Engel curves, suggesting the BLS does not fully net out the impact of quality upgrading. We estimate that annual quality growth averages 3.7 percent for our goods, with 2.2 percent showing up as higher inflation.

The expansion of variety in consumer and intermediate goods plays a central role in many theoretical models of growth. Examples include Paul M. Romer (1990), Gene M. Grossman and Elhanan Helpman (1991 Ch. 3), and Robert J. Barro and Xavier Sala-i-Martin (1995 Ch. 6). In contrast, evidence on variety growth is very sparse. Jerry A. Hausman (1997) and Amil Petrin (1999) estimate the consumer gains to the introduction of specific brands of specific products (Apple-Cinnamon Cheerios and minivans, respectively). Similarly, Manuel Trajtenberg (1989) and Hausman (1999) estimate the gains from computed tomography (CT) scanners and cellular phones, respectively. However, quantifying the aggregate importance of new products on a good-by-good basis is probably not feasible. In particular, it is not possible to obtain data to estimate consumer surplus from the myriad of new models and features that are continually introduced. Reflecting these problems, the Boskin Commission (1996) offers only a few, often speculative, calculations in addressing the issue of variety gains. We take an indirect approach. We exploit how new varieties alter spending patterns, drawing expenditures away from comparatively dormant categories. Table 1 illustrates for a few cases of dramatic product innovations. As the table shows, rapid growth in spending on cable television since 1980 has fueled a broad increase in spending on television, despite a relative decline in spending on television sets. Similarly, VCR’s and movie rentals have spurred an increase in overall spending on movies at home and theaters, personal computers have brought about increased spending on home audio and video equipment, and cell phone services have been responsible for the increased spending on all telephone services. In the 20 years prior to the ascendance of these major new items, all of their categories were stagnant or in relative decline. More generally, we find that consumers have been rapidly shifting away from “static” categories (i.e., those in which there has been little variety or quality gain). This shift far exceeds what can be explained by the impact of relative Engel curves or relative price changes. Our results suggest that variety has increased by perhaps 1 percent per year over the past 40 years. More striking is that most of this growth occurs in just the past 20 years—explaining our title. Looking across 106 more detailed categories, we relate share changes to U.S. Bureau of Labor Statistics (BLS) item-substitution rates. Itemsubstitution rates measure how often the BLS replaces an item in the pricing basket with another model because the former has disappeared from a sample outlet. Frequent BLS item substitutions predict increased spending on a category, even after controlling for Engel-curve, price, and demographic effects. This suggests that new varieties do increase spending on a category, as well as drive out or replace incumbent varieties. Compared to Engel curves, we find that item-substitution rates are a more reliable predictor of shifts in spending shares across goods. Related to this, we question Bruce W. Hamilton (1998) and Dora Costa’s (2000) reliance on food’s share and food’s Engel curve to measure the true rate of U.S. economic growth.

A number of economists find that growth and schooling are highly correlated across countries. A model is examined in which the ability to build on the human capital of one's elders plays an important role in linking growth to schooling. The model is calibrated to quantify the strength of the effect of schooling on growth by using evidence from the labor literature on Mincerian returns to education. The upshot is that the impact of schooling on growth explains less than one-third of the empirical cross-country relationship. The ability of reverse causality to explain this empirical relationship is also investigated.

We examine the frequency of price changes for 350 categories of goods and services covering about 70 percent of consumer spending, on the basis of unpublished data from the Bureau of Labor Statistics for 1995–97. In comparison with previous studies, we find much more frequent price changes, with half of prices lasting less than 4.3 months. Even excluding temporary price cuts (sales), we find that half of prices last 5.5 months or less. We also find that the frequency of price changes differs dramatically across goods. Compared to the predictions of popular sticky‐price models, actual inflation rates are far more volatile and transient for sticky‐price goods.

Consumer theory suggests that expenditures on luxuries and durables should be more cyclical than expenditures on necessities and nondurables. Estimating luxuriouseness and durability for 57 consumer goods, we confirm this prediction in U.S. data. We exploit this finding to test predictions of cyclical utilization and increasing returns models of business cycles. Both models predict more cyclical productivity for durable luxuries, a prediction borne out in the data. The utilization model predicts procyclical relative prices for durables and luxuries; the increasing returns model does not. Prices are more procyclical for durables and luxuries, discriminating in favor of cyclical utilization.

In the United States, the average 40-year-old plant employs more than seven times as many workers as the typical plant 5 years or younger. In contrast, surviving plants in India and Mexico exhibit much slower growth, roughly doubling in size over the same age range. The divergence in plant dynamics suggests lower investments by Indian and Mexican plants in process efficiency, quality, and in accessing markets at home and abroad. In simple general equilibrium models, we find that the difference in life cycle dynamics could lower aggregate manufacturing productivity on the order of 25 percent in India and Mexico relative to the United States.

Resource misallocation can lower aggregate total factor productivity (TFP). We use microdata on manufacturing establishments to quantify the potential extent of misallocation in China and India versus the United States. We measure sizable gaps in marginal products of labor and capital across plants within narrowly defined industries in China and India compared with the United States. When capital and labor are hypothetically reallocated to equalize marginal products to the extent observed in the United States, we calculate manufacturing TFP gains of 30%–50% in China and 40%–60%.in India.

We propose a summary statistic for the economic well-being of people in a country. Our measure incorporates consumption, leisure, mortality, and inequality, first for a narrow set of countries using detailed micro data, and then more broadly using multi-country datasets. While welfare is highly correlated with GDP per capita, deviations are often large. Western Europe looks considerably closer to the United States, emerging Asia has not caught up as much, and many developing countries are further behind. Each component we introduce plays a significant role in accounting for these differences, with mortality being most important.

The positive correlation between real investment rates and real income levels across countries is driven largely by differences in the price of investment relative to output. The high relative price of investment in poor countries is due to the low price of consumption goods in those countries. Investment prices are no higher in poor countries. Thus, the low real investment rates in poor countries are not driven by high tax or tariff rates on investment. Poor countries, instead, appear to be plagued by low efficiency in producing investment goods and in producing consumer goods to trade for them.

The semiconductor industry is often cited as a "strategic" industry in part because important learning-by-doing spillovers may justify special industrial policies. Documenting the precise nature of these spillovers is crucial for determining the advisability of such policies and is helpful for understanding the contribution of learning to endogenous growth. Yet existing empirical evidence on learning by doing in semiconductor production is scant and evidence on spillovers is nonexistent. Using quarterly, firm-level data on seven generations of dynamic random access memory (DRAM) semiconductors over 1974-92, we find that (a) learning rates average 20 percent, (b) firms learn three times more from an additional unit of their own cumulative production than from an additional unit of another firm's cumulative production, (c) learning spills over just as much between firms in different countries as between firms within a given country, (d) Japanese firms are indistinguishable from others in learning speed, and (e) intergenerational learning spillovers are weak, being marginally significant in only two of seven DRAM generations.