Macroeconomic Crises since 1870

history, macroeconomics, crisis, crises

Stock-Market Crashes and Depressions

Long-term data for 30 countries up to 2006 reveal 232 stock-market crashes (multi-year real returns of –25% or less) and 100 depressions (multi-year macroeconomic declines of 10% or more), with 71 of the cases matched by timing. The United States has two of the matched events—the Great Depression 1929–33 and the post-WWI years 1917–21, likely driven by the Great Influenza Epidemic. 41% of the matched cases are associated with war, and the two world wars are prominent. Conditional on a stock-market crash (return of –25% or less) in a non-war environment, the probability of a minor depression (macroeconomic decline of at least 10%) is 22% and of a major depression (at least 25%) is 3%. For contexts of currency or banking crises that occur during times of global distress, these probabilities rise to 46% and 8%, respectively. These depression odds applied to the stock-market crashes of 2008 in the United States and many other countries. In reverse and again in a non-war environment, the probability of a stock-market crash (return of –25% or worse) is 67%, conditional on a depression of 10% or more, and 83% for 25% or more. Thus, the largest depressions are particularly likely to be accompanied by stock-market crashes. We allow for flexible timing between stock-market crashes and depressions for the 71 matched cases to compute the covariance between stock returns and an asset-pricing factor, which depends on the proportionate decline of consumption during a depression. If we assume a coefficient of relative risk aversion around 3.5, this covariance is large enough to account in a familiar looking asset-pricing formula for the observed average (levered) equity premium of 7% per year. This finding complements previous analyses that were based on the probability and size distribution of macroeconomic disasters but did not consider explicitly the covariance between macroeconomic declines and stock returns.

Rare Macroeconomic Disasters

The potential for rare macroeconomic disasters may explain an array of asset-pricing puzzles. Our empirical studies of these extreme events rely on long-term data now covering 28 countries for consumption and 40 for GDP. A baseline model calibrated with observed peak-to-trough disaster sizes accords with the average equity premium with a reasonable coefficient of relative risk aversion. High stock-price volatility can be explained by incorporating time-varying long-run growth rates and disaster probabilities. Business-cycle models with shocks to disaster probability have implications for the cyclical behavior of asset returns and corporate leverage, and international versions may explain the uncovered-interest-parity puzzle. Richer models of disaster dynamics allow for transitions between normalcy and disaster, bring in post-crisis recoveries, and use the full time series on consumption. Potential future research includes applications to long-term economic growth and environmental economics and the use of stock-price options and other variables to gauge time-varying disaster probabilities.

Towards an integral computer environment supporting system operations analysis and conceptual design

VITROCISET has in house developed a prototype tool named System Dynamic Analysis Environment (SDAE) to support system engineering activities in the initial definition phase of a complex space system. The SDAE goal is to provide powerful means for the definition, analysis, and trade-off of operations and design concepts for the space and ground elements involved in a mission. For this purpose SDAE implements a dedicated modeling methodology based on the integration of different modern (static and dynamic) analysis and simulation techniques. The resulting 'system model' is capable of representing all the operational, functional, and behavioral aspects of the system elements which are part of a mission. The execution of customized model simulations enables: the validation of selected concepts with respect to mission requirements; the in-depth investigation of mission specific operational and/or architectural aspects; and the early assessment of performances required by the system elements to cope with mission constraints and objectives. Due to its characteristics, SDAE is particularly tailored for nonconventional or highly complex systems, which require a great analysis effort in their early definition stages. SDAE runs under PC-Windows and is currently used by VITROCISET system engineering group. This paper describes the SDAE main features, showing some tool output examples

Testing the Recovery of Intrinsic Galaxy Sizes and Masses of z~2 Massive Galaxies Using Cosmological Simulations

Accurate measurements of galaxy masses and sizes are key to tracing galaxy evolution over time. Cosmological zoom-in simulations provide an ideal test bed for assessing the recovery of galaxy properties from observations. Here, we utilize galaxies with $M_*\sim10^{10}-10^{11.5}M_{\odot}$ at z~1.7-2 from the MassiveFIRE cosmological simulation suite, part of the Feedback in Realistic Environments (FIRE) project. Using mock multi-band images, we compare intrinsic galaxy masses and sizes to observational estimates. We find that observations accurately recover stellar masses, with a slight average underestimate of ~0.06 dex and a ~0.15 dex scatter. Recovered half-light radii agree well with intrinsic half-mass radii when averaged over all viewing angles, with a systematic offset of ~0.1 dex (with the half-light radii being larger) and a scatter of ~0.2 dex. When using color gradients to account for mass-to-light variations, recovered half-mass radii also exceed the intrinsic half-mass radii by ~0.1 dex. However, if not properly accounted for, aperture effects can bias size estimates by ~0.1 dex. No differences are found between the mass and size offsets for star-forming and quiescent galaxies. Variations in viewing angle are responsible for ~25% of the scatter in the recovered masses and sizes. Our results thus suggest that the intrinsic scatter in the mass-size relation may have previously been overestimated by ~25%. Moreover, orientation-driven scatter causes the number density of very massive galaxies to be overestimated by ~0.5 dex at $M_*\sim10^{11.5}M_{\odot}$.Comment: Published in the Astrophysical Journal Letters (7 pages, 5 figures; updated to match published version

Species Delimitation and Global Biosecurity

Species delimitation directly impacts on global biosecurity. It is a critical element in the decisions made by national governments in regard to the flow of trade and to the biosecurity measures imposed to protect countries from the threat of invasive species. Here we outline a novel approach to species delimitation, “tip to root”, for two highly invasive insect pests, Bemisia tabaci (sweetpotato whitefly) and Lymantria dispar (Asian gypsy moth). Both species are of concern to biosecurity, but illustrate the extremes of phylogenetic resolution that present the most complex delimitation issues for biosecurity; B. tabaci having extremely high intra-specific genetic variability and L. dispar composed of relatively indistinct subspecies. This study tests a series of analytical options to determine their applicability as tools to provide more rigorous species delimitation measures and consequently more defensible species assignments and identification of unknowns for biosecurity. Data from established DNA barcode datasets (COI), which are becoming increasingly considered for adoption in biosecurity, were used here as an example. The analytical approaches included the commonly used Kimura two-parameter (K2P) inter-species distance plus four more stringent measures of taxon distinctiveness, (1) Rosenberg’s reciprocal monophyly, (P(AB)),1 (2) Rodrigo’s (P(randomly distinct)),2 (3) genealogical sorting index, (gsi),3 and (4) General mixed Yule-coalescent (GMYC).4,5 For both insect datasets, a comparative analysis of the methods revealed that the K2P distance method does not capture the same level of species distinctiveness revealed by the other three measures; in B. tabaci there are more distinct groups than previously identified using the K2P distances and for L. dipsar far less variation is apparent within the predefined subspecies. A consensus for the results from P(AB), P(randomly distinct) and gsi offers greater statistical confidence as to where genetic limits might be drawn. In the species cases here, the results clearly indicate that there is a need for more gene sampling to substantiate either the new cohort of species indicated for B. tabaci or to detect the established subspecies taxonomy of L. dispar. Given the ease of use through the Geneious species delimitation plugins, similar analysis of such multi-gene datasets would be easily accommodated. Overall, the tip to root approach described here is recommended where careful consideration of species delimitation is required to support crucial biosecurity decisions based on accurate species identification

Testing stock market convergence: a non-linear factor approach

This paper applies the Phillips and Sul (Econometrica 75(6):1771–1855, 2007) method to test for convergence in stock returns to an extensive dataset including monthly stock price indices for five EU countries (Germany, France, the Netherlands, Ireland and the UK) as well as the US between 1973 and 2008. We carry out the analysis on both sectors and individual industries within sectors. As a first step, we use the Stock and Watson (J Am Stat Assoc 93(441):349–358, 1998) procedure to filter the data in order to extract the long-run component of the series; then, following Phillips and Sul (Econometrica 75(6):1771–1855, 2007), we estimate the relative transition parameters. In the case of sectoral indices we find convergence in the middle of the sample period, followed by divergence, and detect four (two large and two small) clusters. The analysis at a disaggregate, industry level again points to convergence in the middle of the sample, and subsequent divergence, but a much larger number of clusters is now found. Splitting the cross-section into two subgroups including euro area countries, the UK and the US respectively, provides evidence of a global convergence/divergence process not obviously influenced by EU policies

Validation of Cod maturity ogive in NAFO 3M. Effect of the reproductive ccycle moment on ogive estimation.

The Flemish Cap (FC) survey is the source of the Atlantic cod maturity data for SSB estimation. FC survey takes place when females are resting and discrimination between spawning active and inactive females is still possible testing the presence of postovulatory follicles, that remains several months after spawning. However, the best moment for discriminate active spawning females is during the spawning season. For 2012 and 2014, the maturity ogives calculated during the spawning season and when females are resting were compared. Assuming a seasonal growth for cod in 3M, the moment in which maturity is estimated, had no effect on the ogives estimation. Thus, it is recommended to continue employing in the 3M cod assessment the maturity ogives produced with the FC survey information

Regional Income Convergence in Portugal (1991-2002)

Our research aims to address the problem of inequality in income distribution from a different perspective than the usual. We intend to verify if geography influences the pattern of inequality, that is, if the standard of living varies from region to region and if, in the process of growth, spatial units in Portugal have been converging in terms of most relevant variables, such as income. We search the answers to these questions by introducing the treatment of convergence between smaller territorial units, the municipalities as individuals. We intend to evaluate convergence or divergence in income growth and test empirically the theoretical hypothesis that β-convergence, although necessary, is not a sufficient condition for σ-convergence. To study convergence, we use information about GDP and wages for NUTS III regions, and wages for municipalities. We observe spatial dependence between municipalities, so we estimate spatial econometric models to test convergence. With regard to conditional convergence between municipalities, the model most appropriate is the one which includes in the explanatory variables the weight of primary sector employment, leading us to conclude that this variable distinguishes the "steady state" of the small economies. Variables like the activity rate and percentage of active population with higher education also reveal highly significant on the growth of wages, reflecting the different contexts of the labor market at regional level