Financial conditions and the risks to economic growth in the United States since 1875

We explore the historical relationship between financial conditions and real economic growth for quarterly U.S. data from 1875 to 2017 with a flexible empirical copula modelling methodology. We compare specifications with both linear and non-linear dependence, and with both Gaussian and non-Gaussian marginal distributions. Our results indicate strong statistical support for models that are both non-Gaussian and nonlinear for our historical data, with considerable heterogeneity across sub-samples. We demonstrate that ignoring the contribution of financial conditions typically understates the conditional downside risks to economic growth in crises. For example, accounting for financial conditions more than doubles the probability of negative growth in the year following the 1929 stock market crash

The McKenna rule and U.K. World War I finance

The United Kingdom employed the McKenna rule to conduct fiscal policy during World War I (WWI) and the interwar period. Named for Reginald McKenna, Chancellor of the Exchequer (1915–16), the McKenna rule committed the United Kingdom to a path of debt retirement, which we show was forward-looking and smoothed in response to shocks to the real economy and tax rates. The McKenna rule was in the tradition of the “English method” of war finance because the United Kingdom taxed capital to finance WWI. Higher rates of capital taxation also paid for debt retirement during and subsequent to WWI. The United Kingdom was motivated to implement the McKenna rule because of a desire to achieve a balance between fairness and equity. However, the McKenna rule adversely affected the real economy, according to a permanent income model. WWI and interwar U.K. data support the prediction that real activity is lower in response to higher past debt retirement rates.

UK World War I and interwar data for business cycle and growth analysis

This article contributes new time series for studying the UK economy during World War I and the interwar period. The time series are per capita hours worked and average capital income, labor income, and consumption tax rates. Uninterrupted time series of these variables are provided for an annual sample that runs from 1913 to 1938. The authors highlight the usefulness of these time series with several empirical applications. The per capita hours worked data are used in a growth accounting exercise to measure the contributions of capital, labor, and productivity to output growth. The average tax rates are employed in a Bayesian model averaging experiment to reevaluate the Benjamin and Kochin (1979) regression.Business cycles ; Economic development ; Real-time data

U.K. World War I and interwar data for business cycle and growth analysis

This article contributes new time series for studying the U.K. economy during World War I and the interwar period. The time series are per capita hours worked and average tax rates of capital income, labor income, and consumption. Uninterrupted time series of these variables are provided for an annual sample that runs from 1913 to 1938. We highlight the usefulness of these time series with several empirical applications. We use per capita hours worked in a growth accounting exercise to measure the contributions of capital, labor, and productivity to output growth. The average tax rates are employed in a Bayesian model averaging experiment to reevaluate the Benjamin and Kochin (1979) regression.

A Real Time Tax Smoothing Based Fiscal Policy Rule

In this paper we consider the real-time implementation of a fiscal policy rule based on tax smoothing (Barro (1979) and Bohn (1998)). We show that the tax smoothing approach, augmented by fiscal habit considerations, provides a surprisingly accurate description of US budget surplus movements. In order to investigate the robustness of the policy implications of the rule, we construct a real-time US fiscal data set, complementing the data documented by Croushore and Stark (2001). For each variable we record the different vintages, reflecting the remeasurements that occur over time. We demonstrate that the easily constructed rule provided a useful benchmark for policy analysis that is robust to real-time remeasurements

Keep It Real!: A Real-time UK Macro Data Set

In this paper, we present a real-time macro data set for the UK. Each variable has many different vintages---reflecting the revisions that occur in real time. Our aim is to provide a resource that allows researchers to assess the robustness of their results to data revisions. We illustrate the importance of this issue by analysing the impact of real-time data on UK inflation forecasts.

Forecast densities for economic aggregates from disaggregate ensembles

We extend the “bottom up” approach for forecasting economic aggregates with disaggregates to probability forecasting. Our methodology utilises a linear opinion pool to combine the forecast densities from many disaggregate forecasting specifications, using weights based on the continuous ranked probability score. We also adopt a post-processing step prior to forecast combination. These methods are adapted from the meteorology literature. In our application, we use our approach to forecast US Personal Consumption Expenditure inflation from 1990q1 to 2009q4. Our ensemble combining the evidence from 16 disaggregate PCE series outperforms an integrated moving average specification for aggregate inflation in terms of density forecasting.We thank the ARC, Norges Bank, the Reserve Bank of Australia and the Reserve Bank of New Zealand for supporting this research (LP 0991098)

"Keep it real!": A real-time UK macro data set

We present a real-time macro data set for the UK. Each variable has many different vintages - reflecting the revisions and s that occur over time. Our aim is to provide a resource for researchers evaluating UK forecasting performance and policy-making in real time. We illustrate the importance of these data by analysing their impacts on UK inflation forecasts and monetary policy in the late 1980s. We find that, contrary to the view of contemporary policy-makers, the initial measurements of demand-side macro variables did not disguise inflationary pressures.

A Real Time Tax Smoothing Based Fiscal Policy Rule

We consider the real-time implementation of a fiscal policy rule based on tax smoothing (Barro (1979), Bohn (1998)). We show that the tax smoothing approach, augmented by fiscal habit considerations, provides a surprisingly accurate description of US budget surplus movements. In order to investigate the robustness of the policy implications of the rule, we construct a real-time US fiscal data set, complementing the data documented by Croushore and Stark (2001). For each variable, we record the different vintages, reflecting the remeasurements that occur over time. We demonstrate that the rule provides a useful benchmark for policy analysis that is robust to real-time remeasurements.fiscal rules, tax smoothing, fiscal habits, real-time data