In this paper, we undertake a systematic disaggregate analysis of the effects of government spending on economic activity in the US. The level of disaggregation we consider is the highest available and is unprecedented in the empirical literature. More specifically, public consumption and public investment are decomposed into various subcategories, which are measured at the levels of the federal (defence and non‐defence), and state and local governments. For each subcategory, we estimate a structural vector autoregression that identifies public spending shocks through the conditional heteroskedasticity of the structural disturbances, thus relaxing the identifying restrictions commonly used in the literature. Our analysis reveals significant heterogeneity in the effects of public spending shocks on output both across subcategories and government levels. Shocks to spending on durables and structures are found to have the largest and most persistent effect on aggregate output, with a peak multiplier that exceeds 1. Our results also suggest that there is little association between the size of a given category of public expenditures and the magnitude of its effect on output.
Separating the Wheat from the Chaff: A Disaggregate Analysis of the Effects of Public Spending in the USJune 7, 2018
Demographic shifts, such as population ageing, have been suggested as possible explanations for the recent decade-long spell of low inflation. We identify age structure effects on inflation from cross-country variation in a panel of 22 countries from 1870 to 2016 that includes standard monetary factors. We document a robust relationship that is in line with the lifecycle hypothesis: a larger share of dependent population is inflationary, whereas a larger share of working age population is disinflationary. This relationship accounts for the bulk of trend inflation, for instance, about 7 percentage points of US disinflation since the 1980s. It predicts rising inflation over the coming decades.
The growth of novel flexible work formats raises a number of questions about their effects upon health and the potential required changes in public policy. However, answering these questions is hampered by lack of suitable data. This is the first paper that draws on comprehensive longitudinal administrative data to examine the impact of self-employment in terms of health. It also considers an objective measure of health – hospital admissions – that is not subject to recall or other biases that may affect previous studies. Our findings, based on a representative sample of over 100,000 individuals followed monthly from 2005 to 2011 in Portugal, indicate that the likelihood of hospital admission of self-employed individuals is about half that of wage workers. This finding holds even when accounting for a potential self-selection of the healthy into self-employment. Similar results are found for mortality rates.
Financial crises inflict significant human as well as economic hardship. This paper focuses on the human fallout of capital market stress. Financial stress-induced behavioral changes can manifest in higher suicide and murder-suicide rates. We find that these rates also correlate with the Gross Domestic Product (GDP) growth rate (negatively associated; a -0.25% drop [in the rate of change in annual suicides for a 1% change in the independent variable]), unemployment rate (positive link; 0.298% increase), inflation rate (positive link; 0.169% increase in suicide rate levels) and stock market returns adjusted for the risk-free T-Bill rate (negative link; -0.047% drop). Suicides tend to rise during periods of economic turmoil, such as the recent Great Recession of 2008. An analysis of Centers for Disease Control and Prevention (CDC) data of more than 2 million non-natural deaths in the US since 1980 reveals a positive correlation with unemployment levels. We find that suicides and murder-suicides associated with adverse market sentiment lag the initial stressor by up to two years, thus opening a policy window for government/public health intervention to reduce these negative outcomes. Both our models explain about 73 to 76% of the variance in suicide rates and rate of change in suicide rates, and deploy a total of four widely available independent variables (lagged and/or transformed). The results are invariant to the inclusion/exclusion of 2008 data over the 1980-2016 time series, the period of our study. The disconnect between rational decision making, induced by cognitive dissonance and severe financial stress can lead to sub optimal outcomes, not only in the area of investing, but in a direct loss of human capital. No economic system can afford such losses. Finance journal articles focus on monetary alpha, which is the return on a portfolio in excess of the benchmark; we think it is important to be aware of the loss of human capital as a consequence of market instability. This study makes one such an attempt.
A new round has opened in the debate over whether recessions are good or bad for public health. Some researchers have found that death rates fall during recessions. But a new study argues such findings may be distorted by migration, as people move away from places that have fallen on hard times and flock to places with booming economies.
This analysis summarizes prior research and uses national, state and county level data from the United States from 1976-2013 to examine whether the mortality effects of economic crises differ in kind from those of the more typical fluctuations. The tentative conclusion is that economic crises affect mortality rates (and presumably other measures of health) in the same way as less severe downturns: namely, they lead to improvements in physical health. The effects of severe national recessions in the United States, appear to have a beneficial effect on mortality that is roughly twice as strong as that predicted due to the elevated unemployment rates alone while the higher predicted rate of suicides during typical periods of economic weakness is approximately offset during severe recessions. No consistent pattern is obtained for more localized economic crises occurring at the state level – some estimates suggest larger protective mortality effects while others indicate offsetting deleterious consequences.
Estimating the Recession-Mortality Relationship When Migration Matters by Vellore Arthi, Brian Beach, William Walker Hanlon :: SSRNJune 24, 2017
A large literature following Ruhm (2000) suggests that mortality falls during recessions and rises during booms. The panel-data approach used to generate these results assumes that either there is no substantial migration response to temporary changes in local economic conditions, or that any such response is accurately captured by intercensal population estimates. To assess the importance of these assumptions, we examine two natural experiments: the recession in cotton textile-producing districts of Britain during the U.S. Civil War, and the coal boom in Appalachian counties of the U.S. that followed the OPEC oil embargo in the 1970s. In both settings, we find evidence of a substantial migratory response. Moreover, we show that estimates of the relationship between business cycles and mortality are highly sensitive to assumptions related to migration. After adjusting for migration, we find that mortality increased during the cotton recession, but was largely unaffected by the coal boom. Overall, our results suggest that migration can meaningfully bias estimates of the impact of business-cycle fluctuations on mortality.