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Founded in 1920, the National Bureau of Economic Research is a private, nonprofit, nonpartisan research organization dedicated to promoting a greater understanding of how the economy works. The NBER is committed to undertaking and disseminating unbiased economic research among public policymakers, business professionals, and the academic community. Over the years the NBER's research agenda has encompassed a wide variety of issues that confront our society. Early research focused on the aggregate economy, examining in detail the business cycle and long-term economic growth. Simon Kuznets' pioneering work on national income accounting, Wesley Mitchell's influential study of the business cycle, and Milton Friedman's research on the demand for money and the determinants of consumer spending were among the early studies done at the NBER. Toward a Firmer Basis of Economic Policy: The Founding of the National Bureau of Economic Research, Solomon Fabricant, 1984
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    The Centers for Medicare and Medicaid Services (CMS) has phased in the Hierarchical Condition Categories (HCC) risk adjustment model during 2004-2006 to more accurately estimate capitated payments to Medicare Advantage (MA) plans to reflect each beneficiary's health status. However, it is debatable whether the CMS-HCC model has led to strategic evolutions of risk selection. We examine the competing claims and analyze the risk selection behavior of MA plans in response to the CMS-HCC model. We find that the CMS-HCC model reduced the phenomenon that MA plans avoid high-cost beneficiaries in traditional Medicare plans, whereas it led to increased disenrollment of high-cost beneficiaries, conditional on illness severity, from MA plans. We explain this phenomenon in relation to service-level selection. First, we show that MA plans have incentives to effectuate risk selection via service-level selection, by lowering coverage levels for services that are more likely to be used by beneficiaries who could be unprofitable under the CMS-HCC model. Then, we empirically test our theoretical prediction that compared to the pre-implementation period (2001-2003), MA plans have raised copayments disproportionately more for services needed by unprofitable beneficiaries than for other services in the post-implementation period (2007-2009). This induced unprofitable beneficiaries to voluntarily dis-enroll from their MA plans. Further evidence supporting this selection mechanism is that those dissatisfied with out-of-pocket costs were more likely to dis-enroll from MA plans. We estimate that such strategic behavior led MA plans to save $5.2 billion by transferring the costs to the federal government.

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    A new survey of 745 small businesses shows little change in the size distribution of businesses between 2012 and 2016, except among businesses with 40-74 employees, in a way that is closely related to whether they offer health insurance coverage. Using measures of both size and voluntary regulatory compliance, the paper links these changes to the Affordable Care Act's employer mandate. Between 28,000 and 50,000 businesses nationwide appear to be reducing their number of full-time-equivalent employees to below 50 because of that mandate. This translates to roughly 250,000 positions eliminated from those businesses.

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    This paper looks at the effects of air pollution on migration in China using changes in the average strength of thermal inversions over five-year periods as a source of exogenous variation for medium-run air pollution levels. Our findings suggest that air pollution is responsible for large changes in inflows and outflows of migration in China. More specifically, we find that independent changes in air pollution of the magnitude that occurred in China in the course of our study (between 1996 and 2010) are capable of reducing floating migration inflows by 50 percent and of reducing population through net outmigration by 5 percent in a given county. We find that these inflows are primarily driven by well educated people at the beginning of their professional careers, leading to substantial changes in the sociodemographic composition of the population and labor force of Chinese counties. Our results are robust to different specifications, including simple counts of inversions as instruments, different weather controls, and different forms of error variance.

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    In medicine, the reasons for variation in treatment rates across hospitals serving similar patients are not well understood. Some interpret this variation as unwarranted, and push standardization of care as a way of reducing allocative inefficiency. However, an alternative interpretation is that hospitals with greater expertise in a treatment use it more because of their comparative advantage, suggesting that standardization is misguided. We develop a simple economic model that provides an empirical framework to separate these explanations. Estimating this model with data on treatments for heart attack patients, we find evidence of substantial variation across hospitals in both allocative inefficiency and comparative advantage, with most hospitals overusing treatment in part because of incorrect beliefs about their comparative advantage. A stylized welfare-calculation suggests that eliminating allocative inefficiency would increase the total benefits from this treatment by about a third.

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    We assess the role of land markets on factor misallocation in Ethiopia--where land is owned by the state--by exploiting policy-driven variation in land rentals across time and space arising from a recent land certification reform. Our main finding from detailed micro data is that land rentals significantly reduce misallocation and increase agricultural productivity. These effects are nonlinear across farms--impacting more those farms farther away from their efficient operational scale. The effect of land rentals on productivity is 70 percent larger when controlling for non-market rentals--those with a pre-harvest rental rate of zero. Land rentals significantly increase the adoption of new technologies, especially fertilizer use.

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    Some choices in energy regulation, particularly those that price emissions, raise household energy prices more than others. Those choices can lead to a large variation in burden both across and within income groups because of wide variation in household energy use. The latter, within-income group variation can be particularly hard to remedy. In this paper, we review alternative welfare perspectives that give rise to equity concerns within income groups ("horizontal equity") and consider how they might influence the evaluation of environmental policies. In particular, we look for sufficient statistics that policymakers could use to make these evaluations. We use Consumer Expenditure Survey data to generate such statistics for a hypothetical carbon price versus tradable carbon performance standard applied to the electric power sector. We show how horizontal equity concerns could overwhelm efficiency concerns in this context.

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    We propose a simple informational theory to explain why autocratic regimes introduce local elections. Because citizens have better information on local officials than the distant central government, delegation of authority via local elections improves selection and performance of local officials. However, local officials under elections have no incentive to implement unpopular centrally mandated policies. The model makes several predictions: i) elections pose a trade-off between performance and vertical control; ii) elections improve the selection of officials; and iii) an increase in bureaucratic capacity reduces the desirability of elections for the autocrat. To test (i) and (ii), we collect a large village-level panel dataset from rural China. Consistent with the model, we find that elections improve (weaken) the implementation of popular (unpopular) policies, and improve official selection. We provide a large body of qualitative and descriptive evidence to support (iii). In doing so, we shed light on why the Chinese government has systematically undermined village governments twenty years after they were introduced.

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    We develop a theory of sovereign risk contagion based on financial links. In our multi-country model, sovereign bond spreads comove because default in one country can trigger default in other countries. Countries are linked because they borrow, default, and renegotiate with common lenders, and the bond price and recovery schedules for each country depend on the choices of other countries. A foreign default increases the lenders' pricing kernel, which makes home borrowing more expensive and can induce a home default. Countries also default together because by doing so they can renegotiate the debt simultaneously and pay lower recoveries. We apply our model to the 2012 debt crises of Italy and Spain and show that it can replicate the time path of spreads during the crises. In a counterfactual exercise, we find that the debt crisis in Spain (Italy) can account for one-half (one-third) of the increase in the bond spreads of Italy (Spain).

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    We propose a new hypothesis, the Power of Certainty, to help explain agents' difficulties in making choices when there are multiple possible payoff-relevant states. In the probabilistic 'Acquiring-a-Company' problem an agent submits a price to a firm before knowing whether the firm is of low or high value. We construct a deterministic problem with a low and high value firm, where the agent submits a price that is sent to each firm separately. Subjects are much more likely to use dominant strategies in deterministic than in probabilistic problems, even though computations for profit maximization are identical for risk-neutral agents.

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    We adapt simple tools from computational linguistics to construct a new measure of political risk faced by individual US firms: the share of their quarterly earnings conference calls that they devote to political risks. We validate our measure by showing that it correctly identifies calls containing extensive conversations on risks that are political in nature, that it varies intuitively over time and across sectors, and that it correlates with the firm's actions and stock market volatility in a manner that is highly indicative of political risk. Firms exposed to political risk retrench hiring and investment and actively lobby and donate to politicians. Interestingly, we find that the incidence of political risk across firms is far more heterogeneous and volatile than previously thought. The vast majority of the variation in our measure is at the firm-level rather than at the aggregate or sector-level, in the sense that it is neither captured by time fixed effects and the interaction of sector and time fixed effects, nor by heterogeneous exposure of individual firms to aggregate political risk. The dispersion of this firm-level political risk increases significantly at times with high aggregate political risk. Decomposing our measure of political risk by topic, we find that firms that devote more time to discussing risks associated with a given political topic tend to increase lobbying on that topic, but not on other topics, in the following quarter.

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    We present evidence about the ways that school superintendents add value in Israel's primary and middle schools. Superintendents are the CEOs of a cluster of schools with powers to affect the quality of schooling, and we extend the approach used in recent literature to measure teachers' value added, to assess school superintendents. We exploit a quasi-random matching of superintendent and schools, and estimate that superintendent value added has positive and significant effects on primary and middle school students' test scores in math, Hebrew, and English. One standard deviation improvement in superintendent value added increases test scores by about 0.04 of a standard deviation in the test score distribution. The effect doesn't vary with students' socio-economic background, is highly non-linear, increases sharply for superintendents in the highest-quartile of the value added distribution, and is larger for female superintendents. We explore several mechanisms for these effects and find that superintendents with higher value added are associated with more focused school priorities and more clearly defined working procedures, but no effect on school resources and no effect on total teachers' on the job and external training, although there is a significant effect on the composition of the former. Another important effect is that schools with higher quality superintendents are more likely to address school climate, violence and bullying, and implement related interventions which lead to lower violence in school. A new superintendent is also associated with a higher likelihood that the school principal is replaced.

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    Recent decades have seen the emergence of global value chains (GVCs), in which production stages for individual goods are broken apart and scattered across countries. Stimulated by these developments, there has been rapid progress in data and methods for measuring GVC linkages. The macro-approach to measuring GVCs connects national input-output tables across borders using bilateral trade data to construct global input-output tables. These tables have been applied to measure trade in value added, the length of and location of producers in GVCs, and price linkages across countries. The micro-approach uses firm-level data to document firms' input sourcing decisions, how import and export participation are linked, and how multinational firms organize their production networks. In this review, I evaluate progress on these two tracks, highlighting points of contact between them and areas that demand further work. I argue that further convergence between them can strengthen both, yielding a more complete empirical portrait of GVCs.

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    Precision medicines - therapies that rely on genetic, epigenetic, and protein biomarkers - create a better match between individuals with specific disease subtypes and medications that are more effective for those patients. These treatments are expected to be both more effective and more expensive than conventional therapies, implying that their introduction is likely to have a meaningful effect on health care spending patterns. In addition, precision medicines can change the expected profitability of therapies both by allowing more sophisticated pricing systems and potentially decreasing the costs of drug development through shorter and more focused trials. As a result, this could change the types of products that can be profitably brought to market. To better understand the landscape of precision medicines, we use a comprehensive database of over 130,000 global clinical trials, over the past two decades. We identify clinical trials for likely precision medicines (LPMs) as those that use one or more relevant biomarkers. We then further segment trials based on the nature of the biomarker(s) used and other trial features with economic implications. Given potential changes in the incentives for bringing products to market, we also examine the relative importance of public agencies such as the National Institutes of Health (NIH) and different types of private firms in developing precision medicines.

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    The advent of hydraulic fracturing lead to a dramatic increase in US oil production. Due to regulatory, shipping and processing constraints, this sudden surge in domestic drilling caused an unprecedented divergence in crude acquisition costs across US refineries. We take advantage of this exogenous shock to input costs to study the nature of competition and the incidence of cost changes in this important industry. We begin by estimating the extent to which US refining's divergence from global crude markets was passed on to consumers. Using rich microdata, we are able to decompose the effects of firm-specific, market-specific and industry-wide cost shocks on refined product prices. We show that this distinction has important economic and econometric significance, and discuss the implications for prospective policy which would put a price on carbon emissions. The implications of these results for perennial questions about competition in the refining industry are also discussed.

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    We analyze bidding data from uniform price auctions of U.S. Treasury bills and notes between July 2009-October 2013. Primary dealers consistently bid higher yields compared to direct and indirect bidders. We estimate a structural model of bidding that takes into account informational asymmetries introduced by the bidding system employed by the U.S. Treasury. While primary dealers' estimated willingness-to-pay is higher than direct and indirect bidders', their ability to bid-shade is even higher, leading to higher yield/lower price bids. Total bidder surplus averaged to about 3 basis points across the sample period along with efficiency losses around 2 basis points.

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    Statistical agencies typically impute inflation for disappearing products based on surviving products, which may result in overstated inflation and understated growth. Using U.S. Census data, we apply two ways of assessing the magnitude of "missing growth" for private nonfarm businesses from 1983-2013. The first approach exploits information on the market share of surviving plants. The second approach applies indirect inference to firm-level data. We find: (i) missing growth from imputation is substantial - at least 0.6 percentage points per year; and (ii) most of the missing growth is due to creative destruction (as opposed to new varieties).

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    We quantify the impact on U.S. employment from imports and exports during 1995-2011, using the World Input-Output Database. We find that the growth in U.S. exports led to increased demand for 2 million jobs in manufacturing, 0.5 million in resource industries, and a remarkable 4.1 million jobs in services, totaling 6.6 million. One-third of those service sector jobs are due to the intermediate demand from merchandise (manufacturing and resource) exports, so the total labor demand gain due to merchandise exports was 3.7 million jobs. In comparison, U.S. merchandise imports from China led to reduced demand of 1.4 million jobs in manufacturing and 0.6 million in services (with small losses in resource industries), with total job losses of 2.0 million. It follows that the expansion in U.S. merchandise exports to the world relative to imports from China over 1995-2011 created net demand for about 1.7 million jobs. Comparing the growth of U.S. merchandise exports to merchandise imports from all countries, we find a fall in net labor demand due to trade, but comparing the growth of total U.S. exports to total imports from all countries, then there is a rise in net labor demand because of the growth in service exports.

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    Orphan Drug (OD) legislation has been implemented with regulatory and financial incentives to encourage drug innovation in order to treat rare diseases. This study aims to test whether OD Designations (ODD) granted by the Food and Drug Administration (FDA) to pharmaceutical and biotechnology start-up companies may be considered as relevant signals in attracting entrepreneurial finance and increasing the amount invested at the time of the Initial Public Offering (IPO) in the US stock markets. We found that the signaling power of ODD is positively and statistically significant for IPO investors in stock markets. Regression results also suggest that ODDs are stronger than patent applications in attracting IPO investors. Scholarly and policy implications are discussed in the light of the signaling theory and drug development policies.

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    Precision medicines inherently fragment treatment populations, generating small-population markets, creating high-priced "niche busters" rather than broadly prescribed "blockbusters". It is plausible to expect that small markets will attract limited entry in which a small number of interdependent differentiated product oligopolists will compete, each possessing market power. Multiple precision medicine market situations now resemble game theory constructs such as the prisoners' dilemma and Bertrand competition. The examples often involve drug developer choices created by setting the cut-off value for the companion diagnostics to define the precision medicine market niches and their payoffs. Precision medicine game situations may also involve payers and patients who attempt to change the game to their advantage or whose induced behaviors alter the payoffs for the developers. The variety of games may predictably array themselves across the lifecycle of each precision medicine indication niche and so may become linked into a sequentially evolving meta-game. We hypothesize that certain precision medicine areas such as inflammatory diseases are becoming complex simultaneous multi-games in which distinct precision medicine niches compete. Those players that learn the most rapidly and apply those learnings the most asymmetrically will be advantaged in this ongoing information pharms race.

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    New large-scale data linking projects are revolutionizing empirical social science. Outside of selected samples and tightly restricted data enclaves, little is known about the quality of these "big data" or how the methods used to create them shape inferences. This paper evaluates the performance of commonly used automated record-linking algorithms in three high quality historical U.S. samples. Our findings show that (1) no method (including hand linking) consistently produces samples representative of the linkable population; (2) automated linking tends to produce very high rates of false matches, averaging around one third of links across datasets and methods; and (3) false links are systematically (though differently) related to baseline sample characteristics. A final exercise demonstrates the importance of these findings for inferences using linked data. For a common set of records, we show that algorithm assumptions can attenuate estimates of intergenerational income elasticities by almost 50 percent. Although differences in these findings across samples and methods caution against the generalizability of specific error rates, common patterns across multiple datasets offer broad lessons for improving current linking practice.