We develop a framework for modelling conditional loss distributions through the introduction of risk factor dynamics. Asset value changes of a credit portfolio are linked to a dynamic global macroeconometric model, allowing macro effects to be isolated from idiosyncratic shocks. Default probabilities are driven primarily by how firms are tied to business cycles, both domestic and foreign, and how business cycles are linked across countries. The model is able to control for firm-specific heterogeneity as well as generate multi-period forecasts of the entire loss distribution, conditional on specific macroeconomic scenarios.
We presents a global model linking individual country vector error-correcting models in which domestic variables are related to country-specific variables as an approximate solution to a global common factor model. The model is estimated for 26 economies. It provides a theoretical framework where the GVAR is derived as an approximation to a global unobserved common factor model, and using average pair-wise cross-section error correlations, the approach is shown to be quite effective in dealing with common factor interdependencies and international co-movements of business cycles. In addition to generalised impulse response functions, we propose an identification scheme to derive structural impulse responses. We focus on identification of shocks to the US economy, particularly the monetary policy shocks, and consider the time profiles of their effects on the euro area. To this end we include the US model as the first country model and consider alternative orderings of the US variables.
We propose a methodological approach to the forecast and evaluation of multivariate distributions with time varying parameters. For reasons related to feasible inference attention is restricted to meta-elliptical distributions. We use our approach for the study of a large data set of 16 commodity prices. Our approach leads to a theory for model validation avoiding common problems caused by discontinuities, time variation of parameters and nuisance parameters.
This paper provides a synthesis and further development of a global modelling approach introduced in Pesaran, Schuermann and Weiner (2004), where country specific models in the form of VARX* structures are estimated relating a vector of domestic variables to their foreign counterparts and then consistently combined to form a Global VAR (GVAR). It is shown that VARX* models can be derived as the solution to a dynamic stochastic general equilibrium (DSGE) model where over-identifying long-run theoretical relations can be tested and imposed if acceptable. Similarly, short-run over-identifying theoretical restrictions can be tested and imposed if accepted. The assumption of the weak exogeneity of the foreign variables for the long-run parameters can be tested, where foreign variables can be interpreted as proxies for global factors. Rather than using deviations from ad hoc statistical trends, the equilibrium values of the variables reflecting the long-run theory embodied in the model can be calculated.
Empirical evidence presented in this paper shows that the predictability of inflation at long horizons varies considerably across countries. Both simple theory and empirical evidence suggest that the crucial factor is the extent to which systematic monetary policy succeeds in stabilising the incipient unit root in inflation. The mechanism by which it does this appears, however, to be complicated by strong empirical evidence that nominal interest rates have real effects, which implies that monetary policy need not be so vigorous in reaction to inflation. This helps explain why inflation rates in the US and (especially) Germany have been relatively predictable, despite monetary policy rules which appear to have been barely stabilising. The paper also presents tentative evidence that the power of nominal interest rate effects is inversely related to long-horizon inflation uncertainty, and hence ultimately uncertainty about monetary policy.
If stock prices followed a random walk, uncertainty about future stock prices would be so great that the observed bias towards equities in long-term investment portfolios would be surprising. The good news is that if, as a growing body of research suggests, there is even a weak tendency for stationary valuation indicators to predict future stock prices, long-run returns can become markedly more predictable. This is illustrated in a cointegrating VAR, with Tobin?s q as one of the cointegrating relations. The bad news is a corollary of the good news: q and most other indicators point to massive at the end of 1997, and hence the prospect of weak stock prices well into the next century.
This paper This paper develops a new approach to the problem of testing the existence of a long-run level relationship between a dependent variable and a set of regressors, when it is not known with certainty whether the underlying regressors are trend- or first-difference stationary. The proposed tests are based on standard F- and t-statistics used to test the significance of the lagged levels of the variables in a first-difference regression. Two sets of asymptotic critical values are provided: one set assuming that all the regressors are I(1) and another set assuming they are all I(0). These two sets of critical values provide a band covering all possible classifications of the regressors into I(0), I(1) or mutually cointegrated. Accordingly, various bounds testing procedures are proposed. The empirical relevance of the bounds procedures is demonstrated by a re-examination of the earnings equation included in the UK Treasury macro-econometric model. This is a particularly relevant application as there is considerable doubt concerning the order of integration of variables such as the unemployment rate, union strength and the wedge between the real product wage' and the real consumption wage' that enter the earnings equation
This paper compares the effects of weather shocks on agricultural production in Britain, France and Germany during the late nineteenth century. Using semi- parametric models to estimate the non-linear agro-weather relationship, we find that weather shocks explain between one and two-thirds of variations in agricultural production. Given the large size of the agricultural sector during this period, the high variance of agricultural production and the cyclical nature of weather shocks, the agro-weather relationship transmitted large effects on macroeconomic fluctuations over much of the period.
This paper presents substantial new evidence on the competitive process that links together industrial economic and international economics. Our time-series data base concerns manufactured product prices and their domestic and international determinants. We identity cointegrating relationships, using single equation and multivariate methods. We find that both market imperfections, largely ignored in international economics, and international factors, mostly neglected in industrial economics, should be jointly incorporated into pricing analysis. The significance of global factors varies markedly: differentiated-product sectors respond little to foreign price signals. Our findings are relevant to many fields within economics, including the transmission of inflation.
This paper proposes a pair-wise approach to testing for output convergence that considers all N(N-1)/2 possible pairs of log per capita output gaps across N economies. A general probabilistic definition of output convergence is also proposed. The approach is compatible with individual output series having unit roots, does not involve the choice of a reference country in computation of output gaps, and can be applied when N is large relative to T. The test is applied to output series in the Penn World Tables (1950-2000), and to Maddison's historical series (1870-2000). Overall, the results do not support output convergence and suggest that the findings of convergence clubs in the literature might be spurious. However, significant evidence of growth convergence is found. Non-convergence of log per capita outputs combined with growth convergence suggests that there are important country-specific factors that render output gaps highly persistent.
In theory the potential for credit risk diversification for banks could be substantial. Portfolio diversification is driven broadly by two characteristics: the degree to which systematic risk factors are correlated with each other and the degree of dependence individual firms have to the different types of risk factors. We propose a model for exploring these dimensions of credit risk diversification: across industry sectors and across different countries or regions. We find that full firm-level parameter heterogeneity matters a great deal for capturing differences in simulated credit loss distributions. Imposing homogeneity results in overly skewed and fat-tailed loss distributions. These differences become more pronounced in the presence of systematic risk factor shocks: increased parameter heterogeneity greatly reduces shock sensitivity. Allowing for regional parameter heterogeneity seems to better approximate the loss distributions generated by the fully heterogeneous model than allowing just for industry heterogeneity. The regional model also exhibits less shock sensitivity.
We provide a conceptual framework to analysis counterfactual scenarios using macroeconometric models. We consider UK entry to the euro. We derive conditional probability distributions for the difference between the future realisations of variables of interest subject to UK entry restrictions being fully met over a given period, and the alternative realisations without the restrictions. Economic interdependence means that such policy evaluation must take account of international linkages and common factors that drive fluctuations across economies. We use the Global VAR developed by Dees, di Mauro, Pesaran and Smith (2005). The paper briefly describes the GVAR which has been estimated for 25 countries and the euro area over the period 1979-2003. It reports probability estimates that output will be higher and prices lower in the UK and the euro area as a result of entry. It examines the sensitivity of these results to a variety of assumptions about UK entry.
Eight small businesses in the electronics industry from Rochester, NY were studied in
order to determine whether the European Union’s directives, Waste Electrical and
Electronic Equipment (WEEE) and Restriction of Hazardous Substances Directives
(RoHS) are spurring innovation in the US. Innovation was defined as any change in the
design and manufacturing of the products, in the internal organizational structure and
management of the business, or in the market strategies pursued by the small businesses
that created a benefit beyond RoHS and WEEE compliance. Because WEEE and RoHS
are based upon extended producer responsibility principles, this innovation would
complement the findings of previous research completed on extended producer
responsibility (EPR) legislation.
A case study with an in-depth interview was conducted for each of the eight companies to
gather data on the changes the companies had taken in their operational, design, and
management systems to comply with WEEE and RoHS. The collected data was analyzed
to determine which of the changes were “spillover effects” that went beyond the
requirements of WEEE and RoHS.
The analysis led to the finding that the directives were in fact leading to innovations
within each of the companies. While some companies had more profound innovations
Empirical evidence linking exports to economic growth has been mixed and inconclusive. This study re-examine the export-led growth (ELG) hypothesis for Canada by testing for Granger causality from exports to national output growth using vector error correction models (VECM) and the augmented vector autoregressive (VAR) methodology developed in Toda and Yamamoto (1995). Application of recent developments in time series modeling and the inclusion of relevant variables omitted in previous studies help clarify the contradictory results from prior studies on the Canadian economy. The empirical results suggest that a long-run steady state exists among the model???s six variables and that Granger causal flow is unidirectional from real exports to real GDP.
Compreender a dinâmica de funcionamento do mercado de milho brasileiro, procedendo a uma investigação dos fatores que afetam as quantidades e preços nesse mercado, é o objetivo deste trabalho. Os testes de raiz unitária foram feitos utilizando-se a metodologia DF-GLS – Dickey Fuller Generalized Least Square – e os de cointegração de Johansen (1988). O modelo estimado, de ajuste pelo preço, foi um Modelo de Autorregressão Vetorial com Correção de Erros – VEC, sendo a identificação feita pelo procedimento de Sims-Bernanke. O estudo permite afirmar que existe forte interação entre os mercados de milho e de soja, mostrando uma relação de complementaridade na oferta e substitutibilidade na demanda, e que fatores macroeconômicos como renda e juros são importantes na determinação dos preços do milho ao produtor e no atacado. Vale ressaltar que os preços externos do milho mostraram relativa importância no processo de formação do preço doméstico do grão.
O artigo apresenta um modelo integrado de tipo econométrico+insumo-produto para previsões de longo prazo da demanda de combustíveis no Brasil. O modelo é baseado na integração por ligação de um modelo vetorial de correção de erros com um modelo de insumo-produto híbrido para a economia brasileira e permite fazer previsões anuais de consumo para quatro grupos de combustível: gasolina, óleo diesel, óleo combustível e álcool. No processo de desenvolvimento, tanto o modelo econométrico quanto o modelo integrado foram submetidos a testes de desempenho preditivo, com o último sendo calibrado para melhor performance, usando-se dados disponíveis para o período de 2004 a 2007. Posteriormente, o modelo integrado é usado para gerar previsões no período de 2008 a 2017. As previsões são baseadas em dois cenários alternativos, um prevendo duração curta, e o outro, duração longa para a atual crise econômica mundial. Os resultados obtidos indicam que, em ambos os casos, ocorrerá significativo aumento da demanda de combustíveis nos próximos 10 anos.
Esse artigo tem dois principais objetivos. Primeiro compara três diferentes técnicas de datação de ciclos para determinar os picos e os vales da produção industrial do Rio Grande do Sul. Os resultados apontaram que, entre 1991-I e 2008-IV, o setor no Estado passou por cinco recessões. Duas tiveram curta duração, de quatro trimestres, e estão associadas a uma taxa de câmbio mais valorizada. Dois outros ciclos recessivos ocorreram em uma conjuntura de crises internacionais. Por fim, a mais longa recessão, que durou oito trimestres, teve como vetor a estiagem que atingiu o Estado. Um segundo objetivo é a determinação de indicadores antecedentes da produção industrial gaúcha. Partindo de mais de 200 séries candidatas, encontra-se que quatro conseguem antecipar a dinâmica cíclica do setor.
A partir de uma análise descritiva dos dados de consumo de gasolina C por estado é possível notar diferentes comportamentos entre os mesmos. Desta forma, a análise de sensibilidade da demanda por gasolina C a variações no preço no Brasil deve considerar essa multiplicidade de respostas. Através de uma abordagem econométrica tradicional de séries de tempo, procura-se, neste artigo, avaliar as diferentes reações a mudanças no preço, mais especificamente, a mudanças no imposto estadual ICMS sobre a gasolina C. O cálculo da elasticidade-imposto permite verificar os efeitos da adoção de políticas públicas estaduais nos planos ambiental e energético.
Introducción: el D-003 es un ingrediente farmacéutico activo purificado a partir de la cera de caña de azúcar (Saccharum officinarum L.) con efectos como reductor del colesterol y antioxidante, el cual está compuesto por una mezcla de ácidos grasos libres saturados de elevado peso molecular, cada uno dentro de un intervalo de concentración específica determinada por cromatografía de gases (CG). La caracterización espectroscópica del D-003, sin embargo, no ha sido previamente informada. Objetivo: caracterizar el ingrediente farmacéutico activo nombrado D-003 de acuerdo con sus espectros ultravioleta (UV), infrarrojo (FTIR), resonancia magnética nuclear (RMN) y de masas (EM). Métodos: se evaluaron muestras de seis lotes de D-003 (CNIC, Cuba) mediante las técnicas de UV, FTIR, RMN-¹H, RMN-13C y CG-EM. Para obtener los espectros de masas de los ácidos del D-003, estos se derivaron como ésteres metílicos y trimetilsilil. La cuantificación de los ácidos grasos libres saturados de elevado peso molecular, analizados como ésteres metílicos, se llevó a cabo por CG con detector de ionización por llama (DILL). Resultados: los espectros UV, IR, RMN-¹H y RMN-13C mostraron que el ingrediente farmacéutico activo D00-3 está constituido por una mezcla de ácidos grasos libres saturados de elevado peso molecular...