Most of the theoretical literature on price-setting behavior deals with the special case in which only a single price is changed. At the retail-store level, at least, where dozens of products are sold by a single price-setter, price-setting policies are not formulated for individual products. This feature of economic behavior raises a host of questions whose answers carry interesting implications. Are price setters staggered in the timing of price changes? Are price changes of different products synchronized within the store? If so, is this a result of aggregate shocks or of the presence of a store- specific component in the cost of adjusting prices? Can observed small changes in prices be rationalized by a menu cost model? We exploit the multiproduct dimension of the dataset on prices used in Lach and Tsiddon (1992a) to explore several of these and other issues. To the best of our knowledge this is the first empirical work on this subject.
The authors use panel data and information about differences in state tax rates to separate the effects of transitory and permanent tax rate changes on capital-gains realizations behavior. The estimated effect of permanent change is substantially smaller than the effect of transitory change. The difference is even larger than differences between estimates from past micro data studies, which have primarily measured the transitory effect, and time-series studies, which have primarily measured the permanent effect. The authors' results resolve a long-standing conflict between micro data and time-series studies of how marginal tax rates affect capital-gains realizations behavior. Copyright 1994 by American Economic Association.
This paper attributes shortages of goods in socialist economies to the soft financial constraints that firms in such economies face. A 'soft budget constraint' problem arises when the state bank is unable to make a credible commitment not to refinance bad projects once some investment costs are sunk. In such a situation, if a consumer good is also demanded by firms as an input and the seller cannot separate firms from households, the high market-clearing price would lead to welfare losses because too many bad projects would start and crowd out household consumption. Copyright 1994 by American Economic Association.
The new growth literature, following Paul M. Romer (1986) and Robert E. Lucas, Jr. (1988) has formulated models in which growth rates can differ systematically across countries. A large empirical literature has used cross-sectional techniques to examine the cause of differences in growth rates.' This paper examines whether this work has used data which have been constructed in such a way as to introduce inadvertently a spurious correlation between growth and income levels. This effect occurs because relative evolve because of different rates of technological progress in different industries. Many of the new growth models assume single goods or goods produced by the same technology, so this phenomenon has so far escaped analysis.. If technological progress is more rapid in some sectors than others, relative will change during the process of development. The change of relative has two effects on measured growth rates. First, the choice of base affects the growth rate; this phenomenon is sometimes called the effect. Second, using any base or weights introduces a spurious correlation between income and growth. Less developed countries would tend to have lower growth rates, not because they grew more slowly, but because of data construction techniques. For the sake of simplicity, these phenomena will be called the Gerschenkron (or the level) effect and the spurious-correlation effect.3 This paper examines the International Comparison Program (ICP) and the Penn World Tables (PWT), which are based on the ICP. The Penn World Tables are the data most widely used in empirical studies of differences in economic growth. Both the ICP and PWT use international prices to adjust for differences in the purchasing power of currencies. These most closely resemble Hungarian prices. Using such tends to produce time series with lower growth rates than those in the national accounts for countries less developed than Hungary; conversely, the growth rates would be higher for countries more developed than Hungary. However, the growth rates of poorer countries are not systematically lower in the Penn World Tables. The paper examines why the growth rates are not distorted and makes some specific recommendations for data construction and use. * Virginia Polytechnic Institute and State University, Blacksburg, VA 24061-0316. Part of this work was supported by a grant from the Institute of International Studies at Brown University and by a summer internship at the Division of International Finance at the Federal Reserve Board. I am grateful to Peter Garber, David Weil, Oded Galor, and anonymous referees for helpful comments. Alan Heston and Robert Summers have also helped me understand ICP and PWT methodology. Of course, I alone am responsible for any mistakes in this paper. IExamples include Steve Dowrick and Duc-Tho Nguyen (1989), Robert J. Barro (1991), J. Bradford De Long and Lawrence H. Summers (1991), and N. Gregory Mankiw et al. (1992). 2A series of papers by Christina D. Romer (1986a,b, 1989) has already emphasized the importance of data construction techniques in another context. 3There is a third effect, a real acceleration effect caused by shifting consumption patterns and the reallocation of resources between sectors. Growth accountants such as Angus Maddison (1987) adjust estimates of total factor productivity for this sort of shift. William J. Baumol et al. (1989) have also referred to this phenomenon. For an analysis in terms of a simple multisector Solow model, see Nuxoll (1992a).
The literature on patent protection assumes a so called "fencepost" system, in which there would be no need to refer to the courts over questions of interpretation. In reality, we observe a myriad of patent infringement suit through which questions of utility, novelty, and nonobviousness are independently ruled on by a court. Therefore, patent litigation accompanying initial imitations can reveal important information about the validity of the contested patents for other potential entrants. This paper explores the implications of such information revelation through patent litigation. It is shown that the payoffs for the patentee and the initial imitator are highly discontinuous in the degree of patent protection. Furthermore, strengthening intellectual property rights is not necessarily desirable for the patentee. The analysis also has implications for interpreting empirical data on imitations lags.
Information about various policy alternatives is dispersed among the individual members of a society. Prior to a vote over the alternatives, some people take costly political action to signal their private information to voters. By informing voting decisions, political action has potential to decrease the likelihood that voters cast 'mistaken' votes. Perhaps surprisingly, preelection communication may be counterproductive. The dispersed information is partially aggregated by the vote and political action may contribute 'noise' to the voting process. In some cases, the voting mechanism is more likely to implement the full-information voting outcome in the absence of preelection political action. Copyright 1994 by American Economic Association.
One of the key puzzles in understanding behavior is not so much why people save-the title of this session-but why people don't save. According to the familiar life-cycle model, households should accumulate wealth to provide for their retirement consumption. The surprising result from the data is the sizable fraction of the population who have accumulated so little, even among those nearing retirement. Given that earnings will almost surely decline when households retire, such behavior can imply poor living standards for the elderly. Some might interpret the low wealth accumulation as being evidence of myopia, irrationality, or a failure of households to enforce mental accounting (Richard Thaler, 1994), while others might view the low level of wealth accumulation as evidence of high individual rates of time preference. Determining the underlying causes of low wealth is crucial for public policies that seek to alleviate low aggregate rates in the United States, as well as policies that seek to buttress the adequacy of financial resources for the elderly. In this paper, we outline what we believe to be the causes of why many people do not save. We conclude by speculating about government policies that may be most effective at encouraging saving. Much of the research examining levels of consumption, saving, and wealth, as well as their responsiveness to policy, has been done using a life-cycle model with the simplifying assumption of perfect certainty. Alan Auerbach and Laurence Kotlikoff (1987), for example, developed a model with 55 overlapping generations of individual lifecycle households, each with empirically plausible age-earnings profiles and utility parameters, and used the model to address tax policy and demographic issues in a regime in which all households are identical within a generation, and all generations know future earnings and interest rates. More recently, a line of inquiry has examined the effects of uncertainty on saving, generally in the context of highly stylized models. This research has shown that, in these models, uninsured earnings uncertainty can alter optimal behavior in a variety of important ways. (For a partial review of this precautionary saving literature, see Hubbard et al. [1994].) In two recent papers (Hubbard et al., 1993, 1994), we have combined these two strands of the literature by examining the implications of a life-cycle model of consumption, saving, and wealth accumulation subject to what we think are the three most important sources of uninsured idiosyncratic risk facing households: uncertainty about earnings, medical expenses, and length of life. Our intent has been to create a realistic model in which families live for many periods, working for part of their lives and retiring later in life. To parameterize the uncertainty facing families, we estimate tDiscussants: Christopher Carroll, Federal Reserve Board; John B. Shoven, Stanford University; Laurence Kotlikoff, Boston University.