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We examine the long-term relationship between economic conditions and population health in Iceland, which has experienced some economically turbulent times in the last years and decades. We use aggregate annual data for 1981-2014. We use three aggregate indicators of economic activity to proxy the economic cycle: unemployment rate, real GDP per capita, and real GDP. Life expectancy at birth, infant mortality, and total mortality as well as four cause-specific mortality rates were used as outcome measures. Our results do not suggest a statistically significant relationship between economic conditions and total mortality, infant mortality, or life expectancy. Different responses between causes of death are found, and in some instances between genders, although statistical significance is low. We do, however, find a consistent and statistically significant relationship for females aged 45-64, where economic downturns are associated with lower all-cause mortality. For the time period studied we do not find a significant relationship between economic cycles and population health, where health is proxied by mortality rates, life expectancy at birth, and infant mortality. Further studies using less extreme health outcomes, such as morbidity rates, are warranted.

We describe the theory and practice of real GDP comparisons across countries and over time. Version 8 of the Penn World Table expands on previous versions in three respects. First, in addition to comparisons of living standards using components of real GDP on the expenditure side, we provide a measure of productive capacity, called real GDP on the output side. Second, growth rates are benchmarked to multiple years of cross-country price data so they are less sensitive to new benchmark data. Third, data on capital stocks and productivity are (re)introduced. Applications including the Balassa-Samuelson effect and development accounting are discussed.

This paper examines the aftermath of postwar financial crises in advanced countries. We construct a new semiannual series on financial distress in 24 OECD countries for the period 1967-2012. The series is based on assessments of the health of countries' financial systems from a consistent, real-time narrative source, and classifies financial distress on a relatively fine scale. We find that the average decline in output following a financial crisis is statistically significant and persistent, but only moderate in size. More important, we find that the average decline is sensitive to the specification and sample, and that the aftermath of crises is highly variable across major episodes. A simple forecasting exercise suggests that one important driver of the variation is the severity and persistence of financial distress itself. At the same time, we find little evidence of nonlinearities in the relationship between financial distress and the aftermaths of crises.

Economists have long recognized that changes in the quality of existing goods and services, along with the introduction of new goods and services, can raise grave difficulties in measuring changes in the real output of the economy. But despite the attention to this subject in the professional literature, there remains insufficient understanding of just how imperfect the existing official estimates actually are. After studying the methods used by the US government statistical agencies as well as the extensive previous academic literature on this subject, I have concluded that, despite the various improvements to statistical methods that have been made through the years, the official data understate the changes of real output and productivity. The official measures provide at best a lower bound on the true real growth rate with no indication of the size of the underestimation. In this essay, I briefly review why national income should not be considered a measure of well-being; describe what government statisticians actually do in their attempt to measure improvements in the quality of goods and services; consider the problem of new products and the various attempts by economists to take new products into account in measuring overall price and output changes; and discuss how the mismeasurement of real output and of prices might be taken into account in considering various questions of economic policy.

We replicate Reinhart and Rogoff (2010A and 2010B) and find that selective exclusion of available data, coding errors and inappropriate weighting of summary statistics lead to serious miscalculations that inaccurately represent the relationship between public debt and GDP growth among 20 advanced economies. Over 1946–2009, countries with public debt/GDP ratios above 90% averaged 2.2% real annual GDP growth, not −0.1% as published. The published results for (i) median GDP growth rates for the 1946–2009 period and (ii) mean and median GDP growth figures over 1790–2009 are all distorted by similar methodological errors, although the magnitudes of the distortions are somewhat smaller than with the mean figures for 1946–2009. Contrary to Reinhart and Rogoff's broader contentions, both mean and median GDP growth when public debt levels exceed 90% of GDP are not dramatically different from when the public debt/GDP ratios are lower. The relationship between public debt and GDP growth varies significantly by period and country. Our overall evidence refutes RR's claim that public debt/GDP ratios above 90% consistently reduce a country's GDP growth.

We present evidence on the differences in the intensity with which ten major technologies are used in 185 countries across the world. We do so by calculating how many years ago these technologies were used in the U.S. with the same intensity as they are used in the countries in our sample. We denote these time lags as technology usage lags and compare them with lags in real GDP per capita. We find that (i) technology usage lags are large, often comparable to lags in real GDP per capita, (ii) usage lags are highly correlated with lags in per-capita income, and (iii) usage lags are highly correlated across technologies. The productivity differentials between the state-of-the-art technologies that we consider and the ones they replace, combined with the usage lags that we document, lead us to infer that differences in the intensity of usage of technologies might account for a large part of cross-country TFP differentials.

Using data on 14 advanced countries between 1870 and 2008 we document two key facts of the modern business cycle: relative to typical recessions, financial crisis recessions are costlier, and more credit-intensive expansions tend to be followed by deeper recessions (in financial crises or otherwise) and slower recoveries. We use local projection methods to condition on a broad set of macro-economic controls to study how past credit accumulation impacts key macro-economic variables such as output, investment, lending, interest rates, and inflation. The facts that we uncover lend support to the idea that financial factors play an important role in the modern business cycle.

Secular stagnation on the supply side takes the form of a slow 1.6 percent annual growth rate of US potential real GDP, roughly half the 3.1 percent annual growth rate of actual real GDP realized from 1972 to 2004. This slowdown stems from a sharp decline in the growth rate of aggregate hours of work and of output per hour. This paper attributes the productivity growth decline to diminishing returns in the digital revolution that had its peak effect business hardware, software, and best practices in the late 1990s but has resulted in little change in those methods over the past decade.

Empirical studies of bilateral foreign direct investment (FDI) activity show substantial differences in specifications with little agreement on the set of included covariates. We use Bayesian statistical techniques that allow one to select from a large set of candidates those variables most likely to be determinants of FDI activity. The variables with consistently high inclusion probabilities include traditional gravity variables, cultural distance factors, relative labour endowments and trade agreements. There is little support for multilateral trade openness, most host-country business costs, host-country infrastructure and host-country institutions. Our results suggest that many covariates found significant by previous studies are not robust. Les études empiriques des déterminants des activités d'investissement direct bilatéral à l'étranger ont des spécifications substantiellement différentes et peu d'accord sur les variables co-reliées incluses. On utilise des techniques statistiques bayesiennes qui permettent de balayer un vaste ensemble de variables à la recherche de celles qui sont davantage susceptibles d'être des déterminants des activités d'investissement direct à l'étranger. Les variables qui se retrouvent de manière régulière dans la liste de haute probabilité d'impact sont les variables reliées à la gravité, les facteurs liés à la distance culturelle, les dotations relatives en facteur travail, et les accords commerciaux. Il y a peu de support pour des variables comme l'ouverture au commerce multilatéral, la plupart des coûts d'affaires, les infrastructures et les institutions dans les pays hôtes. Ces résultats suggèrent que plusieurs co-variations qu'on a jugées significatives dans les études antérieures ne sont pas robustes.

We explore the effect of the sharp and sustained decline after June 2014 in the global price of crude oil (and hence in the U.S. price of gasoline) on U.S. real GDP growth. Our analysis suggests that this decline produced a cumulative stimulus of about 0.9 percent of real GDP by raising private real consumption and non-oil-related business investment, and an additional stimulus of 0.04 percent, reflecting a shrinking petroleum trade deficit. This stimulative effect, however, has been largely offset by a large reduction in real investment by the oil sector. Hence, the net stimulus since June 2014 has been close to zero. We show that the U.S. economy’s response was not fundamentally different from that observed after the oil price decline of 1986. Then as now, the U.S. economy’s response is consistent with standard economic models of the transmission of oil price shocks. We find no evidence that frictions in reallocating capital and labor across sectors or increased uncertainty about the price of gasoline explain the sluggish response of U.S. real GDP growth. Nor do we find evidence of financial contagion, of spillovers from oil-related investment to non-oil-related investment, of an increase in household savings, or of households deleveraging.