Suchergebnisse

A pivotal question in macroeconomics is how output, employment, and price level react tomonetary, fiscal, and productivity shocks, both in business-cycle models and in the data. Sticky prices are often considered as one of the key amplification and propagation mechanisms for such shocks. However, there is still a widespread debate how sticky prices are and why they are sticky. This dissertation sheds a new light on this question. Chapter 1 relies on a relatively understudied measure of price stickiness--cross-sectional dispersion of prices--to distinguish between different models of price rigidity, while Chapter 2 measures price stickiness in online markets. With e-commerce becoming a significantly larger sector of the economy, this is one of the first attempts to understand pricing in online markets from data comparable to those used for brick-and-mortar stores. Since different business-cycle models make conflicting predictions about effects of demand shocks, in Chapter 3 I approach this question empirically by estimating the size of fiscal multipliers from military spending data. Such empirical estimates may help researchers and policymakers to distinguish between various models. In macroeconomic models, the level of price dispersion, which is typically approximatedusing its relationship with inflation, is a central determinant of welfare, the cost of businesscycles, the optimal rate of inflation, and the trade-off between inflation and output stability.While the comovement of price dispersion and inflation implied by standard models is positive,in this dissertation I show that it is actually negative in the data. Chapter 1 shows that salesplay a pivotal role: i) if sales are removed from the data, the comovement of price dispersionand inflation turns positive; ii) models in which price dispersion is due to price rigidity cannotquantitatively match the comovement even for regular prices; iii) the Calvo model with salescan quantitatively match both the negative comovement found in the data and the positivecomovement for regular prices. Finally, I show that models that fail to match the degree ofcomovement in the data can significantly mismeasure welfare and its determinants. Chapter 2 focuses on price-setting practices in online markets examined through the lens ofa novel dataset on price listings and the number of clicks from the Google Shopping Platform.This unique dataset contains information on price quotes and the number of clicks at the dailyfrequency for a broad variety of consumer goods and sellers in the US and UK over the period of nearly two years. This chapter provides estimates of the frequency of price adjustment,price synchronization across sellers and goods, as well as the distribution of the sizes of price changes. It compares the estimates for the case when information on quantity margin is observed--as in the scanner data from brick-and-mortar stores--with the case when it is not,which is typical in the literature on online prices. It concludes that many internet prices thatdo not change often obtain very few clicks. The key findings are the following: First, despitethe cost of price change being negligible, prices appear relatively sticky. Second, if the quantity margin is accounted for, prices are much more flexible. It remains a question why low-demand sellers do not adjust their prices often, yet maintain costly price listings on the platform. Third, in spite of low costs of monitoring competitors' prices and high benefits from doing so--since search costs for consumers are low too--there is little price synchronization across sellers. Fourth, the distribution of the sizes of price changes is characterized by a non-trivial mass around zero, which is inconsistent with the state-dependent models with fixed menu costs, but favors time-dependent models of price adjustment. Hence, online prices change infrequently, by a large amount, and are not synchronized across sellers. In Chapter 3, I use a multi-country dataset on disaggregated military spending to documentthe effect of government expenditure by sector on aggregate output. The data obtainedfrom multiple sources including UN, NATO, and the Stockholm International Peace ResearchInstitute (SIPRI) allow to systematically break down total military expenditure into that ondurables versus nondurables and services for 69 countries within 1950-1997 period. I showthat the spending multiplier is larger when government spends on durables rather than onnondurables or services, which could be due to differences in price flexibility, intertemporalelasticity of substitution, or some other sectoral factors. Although the estimates suffer fromthe lack of precision, the finding is robust across data sources and groups of countries. Quantitatively, the durables multiplier could be up to four times as high as that for nondurablesand services. I use the dataset to estimate the standard spending multiplier as a litmus test,which results in a conventional fiscal multiplier of the size of about 1 ranging from 0.6 to 1.3in different samples of countries.

Using novel data on military spending for 129 countries in the period 1988-2013, this paper provides new evidence on the effects of government spending on output in advanced and developing countries. Identifying government-spending shocks with an exogenous variation in military spending, we estimate one-year fiscal multipliers in the range 0.75-0.85. The cumulative multipliers remain significantly different from zero within three years after the shock. We find substantial heterogeneity in the multipliers across groups of countries. We then explore three potential sources leading to heterogeneous effects of fiscal policy: the state of the economy, openness to trade, and the exchange-rate regime. We find that the multipliers are especially large in recessions, in closed economies, and under a fixed exchange rate. We also discuss other potential reasons for heterogeneous effects of fiscal policy, such as its implementation and coordination with the monetary authority.

Using 25 years of military spending data from more than a hundred countries, this paper provides new evidence on the effect of government spending on output. Following a popular assumption that military spending is unlikely to respond to output at business-cycle frequencies - and exploiting variation in military spending of a significantly larger magnitude than in the previous literature based on U.S. data - we find that the pooled government spending multiplier is small: below 0.2. This estimate, however, masks substantial heterogeneity: the debtfinanced spending multiplier is larger and can be well above 1 if monetary policy is accommodative. The multiplier is especially large in recessions and when the government purchases durables. We also document substantial heterogeneity across countries with the spending multiplier larger in advanced economies and in countries with a fixed exchange rate. The output response to government spending persists for about two to three years. These findings suggest that the effectiveness of fiscal policy depends largely on the economic environment, policy implementation, and the central bank's response, and that the small multipliers found in historical or pooled data are a poor guide to evaluating the effectiveness of a specific stimulus program.

Using panel data on military spending for 125 countries, we document new facts about the effects of changes in government purchases on the real exchange rate, consumption, and current accounts in both advanced and developing countries. While an increase in government purchases causes real exchange rates to appreciate and increases consumption significantly in developing countries, it causes real exchange rates to depreciate and decreases consumption in advanced countries. The current account deteriorates in both groups of countries. These findings are not consistent with standard international business-cycle models. We investigate whether the difference between advanced economies and developing countries in the responses of real exchange rates to spending shocks can be explained by alternative hypotheses.