Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

The 2008 crisis underscored the interconnectedness of the international business cycle, with U.S. shocks leading to the largest global slowdown since the 1930s. We estimate spillover effects across major advanced country regions in a structural VAR (SVAR) using pre-crisis data. Our new method freely estimates the contemporaneous correlation matrix for underlying shocks in the VAR and (uniquely, to our knowledge) the associated uncertainty. Our results suggest that the international business cycle is largely driven by U.S. financial shocks with a significant impact from global shocks, mainly reflecting commodity prices. Other advanced economic regions play a much smaller and regional role in growth spillovers. Our findings are consistent with the emerging evidence on the current crisis.

Business cycles--Econometric models. --- Business cycles--United States--Econometric models. --- United States. --- Econometrics --- Macroeconomics --- Externalities --- Time-Series Models --- Dynamic Quantile Regressions --- Dynamic Treatment Effect Models --- Diffusion Processes --- State Space Models --- Prices, Business Fluctuations, and Cycles: General (includes Measurement and Data) --- Commodity Markets --- Econometrics & economic statistics --- Economic growth --- Spillovers --- Vector autoregression --- Structural vector autoregression --- Business cycles --- Commodity prices --- International finance --- Prices --- United States --- Econometric models.

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This paper uses the strategy and data of Blanchard and Perotti (BP) to identify fiscal shocks and estimate fiscal multipliers for the United States. With these results, it computes the cumulative multiplier of Ramey and Zubairy (2018), now common in the literature. It finds that, contrary to the peak and through multipliers reported by BP, the cumulative tax multiplier is much larger than the cumulative spending one. Hence, the conclusions depend on the definition of multiplier. This methodology is also used to estimate the effects of fiscal shocks on economic activity in eight Latin American countries. The results suggest that the fiscal multipliers vary significantly across countries, and in some cases multipliers are larger than previously estimated.

United States --- Econometrics --- Macroeconomics --- Public Finance --- Fiscal Policy --- Time-Series Models --- Dynamic Quantile Regressions --- Dynamic Treatment Effect Models --- Diffusion Processes --- State Space Models --- National Government Expenditures and Related Policies: General --- Taxation, Subsidies, and Revenue: General --- Econometrics & economic statistics --- Public finance & taxation --- Structural vector autoregression --- Expenditure --- Vector autoregression --- Revenue administration --- Fiscal multipliers --- Econometric analysis --- Fiscal policy --- Expenditures, Public --- Revenue

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

Conventional assessments of debt sustainability in low income countries are hampered by poor data and weaknesses in methodology. In particular, the standard International Monetary Fund-World bank debt sustainability framework relies on questionable empirical assumptions: its baseline projections ignore statistical uncertainty, and its stress tests, which are performed as robustness checks, lack a clear economic interpretation and ignore the interdependence between the relevant macroeconomic variables. This paper proposes to alleviate these problems by pooling data from many countries and estimating the shocks and macroeconomic interdependence faced by a generic, low income country. The paper estimates a panel vector autoregression to trace the evolution of the determinants of debt, and performs simulations to calculate statistics on external debt for individual countries. The methodology allows for the value of the determinants of debt to differ across countries in the long run, and for additional heterogeneity through country-specific exogenous variables. Results in this paper suggest that ignoring the uncertainty and interdependence of macroeconomic variables leads to biases in projected debt trajectories, and consequently, the assessment of debt sustainability.

Bankruptcy and Resolution of Financial Distress --- Bootstrap --- Debt Markets --- Debt sustainability --- Economic Theory & Research --- Emerging Markets --- External Debt --- Finance and Financial Sector Development --- Low income countries --- Macroeconomics and Economic Growth --- Panel vector autoregression

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

The expansionary fiscal contraction (EFC) hypothesis states that fiscal austerity can increase output or consumption when a country is under heavy debt burdens because it sends positive signal about the country's solvency situation and long-term economic wellbeing. Empirical tests of this hypothesis have suffered from identification concerns due to data sources and empirical methodology. Using a sample of OECD countries between 1978 and 2014, this paper combines new IMF narrative data and the proxy structural Vector Auto-regression (SVAR) method to examine whether fiscal austerities can be expansionary when debt levels are high. Fiscal austerities are measured as 1) narrative fiscal shocks and 2) structural shocks from a proxy SVAR. Additionally, this paper uses a model-based approach to determine the cutoff debt level beyond which EFC is expected to be observed. This paper finds empirical evidence in support of the EFC hypothesis for OECD countries: results for output are driven by changes in tax rates and are robust to how one defines a high-debt regime and how one measures austerity.

Austerity --- Debt Burden --- Debt Sustainability --- Economic Crisis --- Economic Shock --- External Debt --- Fiscal Adjustment --- Fiscal Consolidation --- Fiscal Policy --- Fiscal Shock --- International Economics and Trade --- Macroeconomic Management --- Macroeconomics and Economic Growth --- Structural Vector Autoregression

Choose an application

• Reference Manager
• EndNote
• RefWorks (Direct export to RefWorks)

This paper addresses the identification of low-frequency macroeconomic shocks, such as technology, in Structural Vector Autoregressions. Whilst identification issues with long-run restricted VARs are well documented, the recent attempt to overcome said issues using the Max-Share approach of Francis and others (2014) and Barsky and Sims (2011) has its own shortcomings, primarily that they are vulnerable to bias from confounding non-technology shocks. A modification to the Max-Share approach and two further spectral methods are proposed to improve empirical identification. Performance directly hinges on whether these confounding shocks are of high or low frequency. Applied to US and emerging market data, spectral identifications are most robust across specifications, and non-technology shocks appear to be biasing traditional methods of identifying technology shocks. These findings also extend to the SVAR identification of dominant business-cycle shocks, which are shown will be a variance-weighted combination of shocks rather than a single structural driver.

Business Cycle --- Business Cycles and Stabilization Policies --- Economic Conditions and Volatility --- Economic Growth --- Economic Shocks --- Economic Theory and Research --- Macroeconomics and Economic Growth --- Productivity --- Science and Technology Development --- Structural Vector Autoregression --- Technology Innovation --- Technology Shock