Knowledge that Transforms

We review the empirical literature that estimates the causal effect of parent's schooling on child's schooling, and conclude that estimates differ across studies. We then consider three explanations for why this is: (a) idiosyncratic differences in data sets, (b) differences in remaining biases between different identification strategies, and (c) differences across identification strategies in their ability to make out-of-sample predictions. We conclude that discrepancies in past studies can be explained by violations of identifying assumptions. Our reading of past evidence, together with an application to Swedish register data, suggests that intergenerational schooling associations are largely driven by selection. Parental schooling constitutes a large part of the parental nurture effect, but as a whole does not play a large role. (JEL I21, J13)

I survey the male and female labor supply literatures, focusing on implications for effects of wages and taxes. For males, I describe and contrast results from three basic types of model: static models (especially those that account for nonlinear taxes), life-cycle models with savings, and life-cycle models with both savings and human capital. For women, more important distinctions are whether models include fixed costs of work, and whether they treat demographics like fertility and marriage (and human capital) as exogenous or endogenous. The literature is characterized by considerable controversy over the responsiveness of labor supply to changes in wages and taxes. At least for males, it is fair to say that most economists believe labor supply elasticities are small. But a sizable minority of studies that I examine obtain large values. Hence, there is no clear consensus on this point. In fact, a simple average of Hicks elasticities across all the studies I examine is 0.31. Several simulation studies have shown that such a value is large enough to generate large efficiency costs of income taxation. For males, I conclude that two factors drive many of the differences in results across studies. One factor is use of direct versus ratio wage measures, with studies that use the former tending to find larger elasticities. Another factor is the failure of most studies to account for human capital returns to work experience. I argue that this may lead to downward bias in elasticity estimates. In a model that includes human capital, I show how even modest elasticities—as conventionally measured—can be consistent with large efficiency costs of taxation. For women, in contrast, it is fair to say that most studies find large labor supply elasticities, especially on the participation margin. In particular, I find that estimates of “long-run” labor supply elasticities—by which I mean estimates that allow for dynamic effects of wages on fertility, marriage, education and work experience—are generally quite large. (JEL D91, J13, J16, J22, J31, H24)

The paper provides a review of the estimation of structural vector autoregressions with sign restrictions. It is shown how sign restrictions solve the parametric identification problem present in structural systems but leaves the model identification problem unresolved. A market and a macro model are used to illustrate these points. Suggestions have been made on how to find a unique model. These are reviewed. An analysis is provided of whether one can recover the true impulse responses and what difficulties might arise when one wishes to use the impulse responses found with sign restrictions. (JEL C32, C51, E12)

This essay briefly reviews the state of knowledge about the government spending multiplier. Drawing on theoretical work, aggregate empirical estimates from the United States, as well as cross-locality estimates, I assess the likely range of multiplier values for the experiment most relevant to the stimulus package debate: a temporary, deficit-financed increase in government purchases. I conclude that the multiplier for this type of spending is probably between 0.8 and 1.5. (JEL E23, E62, H50)

Are natural resources a “curse” or a “blessing”? The empirical evidence suggests that either outcome is possible. This paper surveys a variety of hypotheses and supporting evidence for why some countries benefit and others lose from the presence of natural resources. These include that a resource bonanza induces appreciation of the real exchange rate, deindustrialization, and bad growth prospects, and that these adverse effects are more severe in volatile countries with bad institutions and lack of rule of law, corruption, presidential democracies, and underdeveloped financial systems. Another hypothesis is that a resource boom reinforces rent grabbing and civil conflict especially if institutions are bad, induces corruption especially in nondemocratic countries, and keeps in place bad policies. Finally, resource rich developing economies seem unable to successfully convert their depleting exhaustible resources into other productive assets. The survey also offers some welfare-based fiscal rules for harnessing resource windfalls in developed and developing economies. (JEL O47, Q32, Q33)

A recent literature has constructed top income shares time series over the long run for more than twenty countries using income tax statistics. Top incomes represent a small share of the population but a very significant share of total income and total taxes paid. Hence, aggregate economic growth per capita and Gini inequality indexes are sensitive to excluding or including top incomes. We discuss the estimation methods and issues that arise when constructing top income share series, including income definition and comparability over time and across countries, tax avoidance, and tax evasion. We provide a summary of the key empirical findings. Most countries experience a dramatic drop in top income shares in the first part of the twentieth century in general due to shocks to top capital incomes during the wars and depression shocks. Top income shares do not recover in the immediate postwar decades. However, over the last thirty years, top income shares have increased substantially in English speaking countries and in India and China but not in continental European countries or Japan. This increase is due in part to an unprecedented surge in top wage incomes. As a result, wage income comprises a larger fraction of top incomes than in the past. Finally, we discuss the theoretical and empirical models that have been proposed to account for the facts and the main questions that remain open. (JEL D31, D63, H26, N30)

China's economic reforms have resulted in spectacular growth and poverty reduction. However, China's institutions look ill-suited to achieve such a result, and they indeed suffer from serious shortcomings. To solve the “China puzzle,” this paper analyzes China's institution—a regionally decentralized authoritarian system. The central government has control over personnel, whereas subnational governments run the bulk of the economy; and they initiate, negotiate, implement, divert, and resist reforms, policies, rules, and laws. China's reform trajectories have been shaped by regional decentralization. Spectacular performance on the one hand and grave problems on the other hand are all determined by this governance structure. (JEL O17, O18, O43, P21, P25, P26)

Economists have shown that large and persistent differences in productivity levels across businesses are ubiquitous. This finding has shaped research agendas in a number of fields, including (but not limited to) macroeconomics, industrial organization, labor, and trade. This paper surveys and evaluates recent empirical work addressing the question of why businesses differ in their measured productivity levels. The causes are manifold, and differ depending on the particular setting. They include elements sourced in production practices—and therefore over which producers have some direct control, at least in theory—as well as from producers' external operating environments. After evaluating the current state of knowledge, I lay out what I see are the major questions that research in the area should address going forward. (JEL D24, G31, L11, M10, O30, O47)