The Macroeconomic Impacts of Natural Disasters: New Evidence from Floods

We analyze the economic impacts of floods using new data on 3,184 large flood events in 118 countries between 1985 and 2008. We use panel vector auto-regressions to trace the dynamic response of output to three types of flood shocks. Our results robustly indicate that flood shocks tend to have a positive average impact on GDP growth, that this impact is limited to developing countries, that the effect is not confined to the agricultural sector, and that it is stronger when it is accompanied by an increase in gross fixed capital formation.Natural Disasters, Floods, VAR, Economic growth, Macroeconomic Shocks, Environmental Economics and Policy, International Development, Public Economics,

Oil Prices, Economic Activity and Inflation: Evidence for Some Asian Countries

In this paper we study the oil prices-macroeconomy relationship by means of studying the impact of oil price shocks on both economic activity and consumer price indexes for six Asian countries over the period 1975Q1-2002Q2. The results suggest that oil prices have a significant effect on both economic activity and price indexes although the impact is limited to the short-run and more significant when oil price shocks are defined in local currencies. Moreover, we find evidence of asymmetries in the oil prices-macroeconomy relationship for some of the Asian countries.

Deterministic Versus Stochastic Seasonal Fractional Integration and structural breaks

This paper considers a general model which allows for both deterministic and stochastic forms of seasonality, including fractional (stationary and nonstationary) orders of integration, and also incorporating endogenously determined structural breaks. Monte Carlo analysis shows that the suggested procedure performs well even in small samples, accurately capturing the seasonal properties of the series, and correctly detecting the break date. As an illustration, the model is estimated for four different US series (output, consumption, imports and exports). The results suggest that the seasonal patterns of these variables have changed over time: specifically, in the second subsample the systematic component of seasonality becomes insignificant, whilst the degree of persistence increases

Modelling Long-Run Trends and Cycles in Financial Time Series Data

This paper proposes a very general time series framework to capture the long-run behaviour of financial series. The suggested model includes linear and non-linear time trends, and stationary and nonstationary processes based on integer and/or fractional degrees of differentiation. Moreover, the spectrum is allowed to contain more than a single pole or singularity, occurring at zero and non-zero (cyclical) frequencies. This model is used to analyse four annual time series with a long span, namely dividends, earnings, interest rates and long-term government bond yields. The results indicate that the four series exhibit fractional integration with one or two poles in the spectrum. A forecasting comparison shows that a model with a non-linear trend along with fractional integration outperforms alternative models over long horizons.fractional integration, financial time series data, trends, cycles

Gait Extraction and Description by Evidence-Gathering

Using gait as a biometric is of increasing interest, yet there are few model-based, parametric, approaches to extract and describe moving articulated objects. One new approach can detect moving parametric objects by evidence gathering, hence accruing known performance advantages in terms of performance and occlusion. Here we show how that the new technique can be extended not only to extract a moving person, but also to extract and concurrently provide a gait signature for use as a biometric. We show the natural relationship between the bases of these approaches, and the results they can provide. As such, these techniques allow for gait extraction and description for recognition purposes, and with known performance advantages of a well-established vision technique

Structural Changes in Volatility and Stock Market Development: Evidence for Spain

In this paper we review the factors that may lead to structural changes in stock market volatility and present an analysis that assesses whether Spanish stock market volatility has changed significantly over the period 1941-2001. This period corresponds to the years of more profound development of both the financial and the productive sides of the economy in this country. We use alternative methodologies of endogenous breakpoint detection that estimate the dates at which the behavior of stock market volatility changed. The analysis of the Spanish stock market suggests that volatility has behaved in a different manner over the period 1941-2001: From 1972 to 2001, the years of more intense development of the stock market, the Spanish stock market has been characterized by a higher level of volatility and a lower persistence. This effect is partly attributable to the increased growth of trading volume brought about by the economic development process

Deterministic versus Stochastic Seasonal Fractional Integration and Structural Breaks

This paper considers a general model which allows for both deterministic and stochastic forms of seasonality, including fractional (stationary and nonstationary) orders of integration, and also incorporating endogenously determined structural breaks. Monte Carlo analysis shows that the suggested procedure performs well even in small samples, accurately capturing the seasonal properties of the series, and correctly detecting the break date. As an illustration, the model is estimated for four different US series (output, consumption, imports and exports). The results suggest that the seasonal patterns of these variables have changed over time: specifically, in the second subsample the systematic component of seasonality becomes insignificant, whilst the degree of persistence increases.deterministic and stochastic seasonality, fractional integration, structural breaks

Is the US Fiscal Deficit Sustainable? A Fractionally Integrated and Cointegrated Approach

The sustainability of fiscal deficits has received in recent years increasing attention from economists. Empirical work has concentrated on both the univariate properties of debt and the cointegration properties of public revenues and expenditures. In this paper, we examine if sustainability of the US fiscal deficit holds by means of studying the univariate properties of the difference between public revenues and expenditures. However, instead of using classical approaches based on I(1) or I(0) integration techniques, we use a methodology based on fractional processes. The results show that the public deficit in the US is an I(d) process with d slightly smaller than 1, implying that fiscal deficit is mean reverting, and thus, sustainable, though the adjustment process towards equilibrium will take a very long time.

Additional Empirical Evidence on Real Convergence: A Fractionally Integrated Approach

This article examines the real convergence hypothesis in 15 OECD countries. For this purpose, we examine the order of integration of the real GDP per capita series in these countries as well as their differences with respect to the US which is used as a benchmark country. We use both parametric and semiparametric methods and the results show that convergence is only achieved in half of the countries, namely, Austria, Australia, Canada, Finland, Germany, Japan and the UK. On the contrary, the results for Belgium, Denmark, France, Italy, the Netherlands, Norway and Sweden show strong evidence against this hypothesis.

The relationship between commodity markets and commodity mutual funds: a wavelet-based analysis

This paper examines the causal relationship between commodities funds and returns using monthly data for the period May 1997–August 2015. Given the strong evidence of nonlinearity and structural breaks, we use wavelets to analyse causality between the two variables at both time and frequency domains. Wavelet coherency reveals that these two variables are primarily positively related in the short-run and over the period of 2008–2015. When we investigate the phase differences over this period, we observe that returns have predicted flows over the period of 2008–2012, with causality running in the other direction thereafter.http://www.elsevier.com/locate/frlhj2019Economic