Synchronisation of financial crises

This paper develops concordance indices for studying the simultaneous occurrence of financial crises. The indices are designed to cope with these typically low incidence events. This leads us to confine attention to non-tranquil periods to develop a bivariate index and its multivariate analog for potentially serially correlated categorical data. An application to the Bordo et al. (2001) data set reveals the extent of concordance in banking and currency crises across countries. The internationalisation of financial crises in the 20th century is shown to have increased for currency crises and decreased for banking crises

Why didn't the Global Financial Crisis hit Latin America?

Latin America has a rich history of financial crises. However, it was relatively unharmed by the 2007-2009 Global Financial Crisis (GFC). This paper investigates why, and in particular the role of commodity prices and its institutional framework - in line with the fourth generation financial crisis model. We set up Early Warning Systems (EWS) for Argentina, Brazil and Mexico. These consist of an ordered logit model for currency crises for the period 1990-2007 with a dynamic factor model to deal with the large number of explanatory variables. We present forecasts for the period 2008-2009. We find that international indicators play an important role in explaining currency crises in Mexico, while banking indicators and commodities explain the currency crisis in Argentina and Brazil. Furthermore, debt and domestic economy indicators are relevant for Argentina and Mexico. Finally, we observe that currency crises in all three countries are related to institutional indicators. For none of the countries the Early Warning System would have issued an early warning for the GFC.Financial crises, Early Warning Systems, Latin America, dynamic factor models, ordered logit model,

Lessons From the Latest Data on U.S. Productivity

La croissance de la productivité est examinée par les macro-économistes car elle joue des rôles clés dans la compréhension de l’épargne dans le secteur privé, les sources des chocs macroéconomiques, l’évolution de la compétitivité internationale et la solvabilité des régimes de retraite publics. Toutefois, les estimations des taux de croissance de la productivité anticipées et conjoncturelles souffrent de deux problèmes potentiels : (i) les estimations des tendances récentes sont imprécises, et (ii) les données récemment publiées subissent souvent d’importantes révisions. Cette étude met en évidence la (non-) fiabilité de plusieurs mesures de croissance de la productivité agrégée aux États-Unis en examinant la mesure dans laquelle elles sont révisées au fil du temps. Nous examinons également dans quelle mesure ces révisions contribuent aux erreurs dans les prévisions de croissance de la productivité des États-Unis. Nous constatons que les révisions de données provoquent généralement des changements appréciables des estimations des taux de croissance de la productivité publiés à travers une gamme de différentes mesures de la productivité. D'importantes révisions surviennent souvent des années après la première publication des données, ce qui contribue significativement à l'incertitude générale à laquelle nos décideurs politiques doivent faire face. Cela souligne le besoin de moyens pour réduire l'incertitude à laquelle sont confrontés les décideurs politiques et les politiques robustes à l'incertitude sur les conditions économiques actuelles. La croissance de la productivité est examinée par les macro-économistes car elle joue des rôles clés dans la compréhension de l’épargne dans le secteur privé, les sources des chocs macroéconomiques, l’évolution de la compétitivité internationale et la solvabilité des régimes de retraite publics. Toutefois, les estimations des taux de croissance de la productivité anticipées et conjoncturelles souffrent de deux problèmes potentiels : (i) les estimations des tendances récentes sont imprécises, et (ii) les données récemment publiées subissent souvent d’importantes révisions. Cette étude met en évidence la (non-) fiabilité de plusieurs mesures de croissance de la productivité agrégée aux États-Unis en examinant la mesure dans laquelle elles sont révisées au fil du temps. Nous examinons également dans quelle mesure ces révisions contribuent aux erreurs dans les prévisions de croissance de la productivité des États-Unis. Nous constatons que les révisions de données provoquent généralement des changements appréciables des estimations des taux de croissance de la productivité publiés à travers une gamme de différentes mesures de la productivité. D'importantes révisions surviennent souvent des années après la première publication des données, ce qui contribue significativement à l'incertitude générale à laquelle nos décideurs politiques doivent faire face. Cela souligne le besoin de moyens pour réduire l'incertitude à laquelle sont confrontés les décideurs politiques et les politiques robustes à l'incertitude sur les conditions économiques actuelles.Productivité, analyses en temps réel, révisions de données, projections Greenbook projections , Productivité, analyses en temps réel, révisions de données, projections Greenbook projections

Does Household Borrowing Reduce the Trade Balance? Evidence from Developing and Developed Countries

We examine the dynamic impact of household borrowing on the trade balance using data from 32 developing countries and 36 developed countries over the 1980-2020 period. Our findings suggest that the impact of household borrowing on the trade balance is negative, both in the short and long run, but the effects are more pronounced in developing countries. Moreover, we find that for developing countries the negative effect of household borrowing on the trade balance is achieved via boosting imports. In developed countries, household borrowing stimulates both imports and exports, where the effect on imports is larger

Towards a financial cycle for the U.S., 1973-2014

With this paper, we suggest a new approach to estimating financial cycles in terms of interactions of real-sector and financial-sector sentiments. We will apply this to U.S. financial indicators from 1973 to 2014. Based on Schumpeter’s and Minsky’s financial cycle concepts, we arrive at a selection of six indicators that capture finance and real sector linkages: the slope of the yield curve, a Purchasing Managers’ Index, real-estate price returns, the S&P stock price index, and leverage ratios of households (consumer spending) and non-financial corporations. We estimate lead-lag relations and apply principal component analysis to aligned series in order to construct factors. Our conclusion is that two factors, capturing corporate and consumer sentiments, account for over 60% of the cumulative variance in our data. Corporate optimism peaks before crisis episodes, while household/consumer sentiment is more persistent and follows corporate sentiment with a lag

Is fiscal policy in the euro area Ricardian?

We empirically determine whether a Ricardian or a non-Ricardian regime is more plausible for the euro area, following the research strategy of Canzoneri et al. (Am Econ Rev 91:1221-1238, 2001). A Vector AutoRegressive model for the primary government balance and the government debt is estimated for the period 1980q2-2013q4. Our model uses dummy interaction terms to account for the breaks due to the introduction of the Euro Convergence Criteria (ECC) and the start of the global financial crisis, respectively. No evidence is found in favour of either regime for the pre-ECC period. In the post-ECC period, a Ricardian regime is more plausible. Some evidence points in the direction of a non-Ricardian regime for the period after the start of the financial crisis

Health and wealth in the Roman Empire

Ancient Rome was the largest and most populous empire of its time, and the largest pre-industrial state in European history. Recent though not universally accepted research suggests that at least for the most populous central periods of its history standard of living was also rather higher than before or after. To trace whether this is also reflected in Roman biological standard of living, we present the first large and more or less comprehensive dataset, based on skeletal data for some 10,000 individuals, covering all periods of Roman history, and all regions (even if inevitably unequally). We discuss both the methodologies that we developed and the historical results. Instead of reconstructing heights from the long bones assuming fixed body proportions or from one individual long bone, we apply exploratory factor analysis and calculate factor scores for 50-year periods. Our measure of the biological standard of living declined during the last two centuries B.C. and started to improve again, slowly at first, from the second century A.D. It correlated negatively with population, but also with other aspects of standard of living such as wages or diets

Can GDP measurement be further improved? Data revision and reconciliation

Recent years have seen many attempts to combine expenditure-side estimates of U.S. real output (GDE) growth with income-side estimates (GDI) to improve estimates of real GDP growth. We show how to incorporate information from multiple releases of noisy data to provide more precise estimates while avoiding some of the identifying assumptions required in earlier work. This relies on a new insight: using multiple data releases allows us to distinguish news and noise measurement errors in situations where a single vintage does not. Our new measure, GDP++, fits the data better than GDP+, the GDP growth measure of Aruoba et al. (2016) published by the Federal Reserve Bank of Philadephia. Historical decompositions show that GDE releases are more informative than GDI, while the use of multiple data releases is particularly important in the quarters leading up to the Great Recession

Can GDP Measurement Be Further Improved? Data Revision and Reconciliation

Recent years have seen many attempts to combine expenditure-side estimates of U.S. real output (GDE) growth with income-side estimates (GDI) to improve estimates of real GDP growth. We show how to incorporate information from multiple releases of noisy data to provide more precise estimates while avoiding some of the identifying assumptions required in earlier work. This relies on a new insight: using multiple data releases allows us to distinguish news and noise measurement errors in situations where a single vintage does not. We find that (a) the data prefer averaging across multiple releases instead of discarding early releases in favor of later ones, and (b) that initial estimates of GDI are quite informative. Our new measure, GDP(++), undergoes smaller revisions and tracks expenditure measures of GDP growth more closely than either the simple average of the expenditure and income measures published by the BEA or the GDP growth measure of Aruoba et al. published by the Federal Reserve Bank of Philadelphia

A criterion for the number of factors

This note proposes a new criterion for the determination of the number of factors in an approximate static factor model. The criterion is strongly associated with the scree test and compares the differences between consecutive eigenvalues to a threshold. The size of the threshold is derived from a hyperbola and depends only on the sample size and the number of factors k. Monte Carlo simulations compare its properties with well-established estimators from the literature. Our criterion shows similar results as the standard implementations of these estimators, but is not prone to a lack of robustness against a too large a priori determined maximum number of factors kmax