Evaluating predictive densities of U.S. output growth and inflation in a large macroeconomic data set

We evaluate conditional predictive densities for U.S. output growth and inflationusing a number of commonly used forecasting models that rely on a large number ofmacroeconomic predictors. More specifically, we evaluate how well conditional predictive densities based on the commonly used normality assumption fit actual realizationsout-of-sample. Our focus on predictive densities acknowledges the possibility that, although some predictors can improve or deteriorate point forecasts, they might have theopposite effect on higher moments. We find that normality is rejected for most modelsin some dimension according to at least one of the tests we use. Interestingly, however,combinations of predictive densities appear to be correctly approximated by a normaldensity: the simple, equal average when predicting output growth and Bayesian modelaverage when predicting inflation.

Brazilian equity risk premium analysis: A macroeconomic approach

Double Degree Masters in Economics Program from Insper and NOVA School of Business and Economics

Using VARs and TVP-VARs with Many Macroeconomic Variables

This paper discusses the challenges faced by the empirical macroeconomist and methods for surmounting them. These challenges arise due to the fact that macroeconometric models potentially include a large number of variables and allow for time variation in parameters. These considerations lead to models which have a large number of parameters to estimate relative to the number of observations. A wide range of approaches are surveyed which aim to overcome the resulting problems. We stress the related themes of prior shrinkage, model averaging and model selection. Subsequently, we consider a particular modelling approach in detail. This involves the use of dynamic model selection methods with large TVP-VARs. A forecasting exercise involving a large US macroeconomic data set illustrates the practicality and empirical success of our approach.

Chapter 4 A Review of the Availability of and Studies on Spatial Economic Data in Laos

Spatial data are being increasingly used in a wide range of disciplines, a fact that is clearly reflected in the recent trend to add spatial dimensions to the conventional social sciences. Economics is by no means an exception. On one hand, spatial data are indispensable to many branches of economics such as economic geography, new economic geography, or spatial economics. On the other hand, macroeconomic data are becoming available at more and more micro levels, so that academics and analysts take it for granted that they are available not only for an entire country, but also for more detailed levels (e.g. state, province, and even city). The term ‘spatial economics data’ as used in this report refers to any economic data that has spatial information attached. This spatial information can be the coordinates of a location at best or a less precise place name as is used to describe administrative units. Obviously, the latter cannot be used without a map of corresponding administrative units. Maps are therefore indispensible to the analysis of spatial economic data without absolute coordinates. The aim of this report is to review the availability of spatial economic data that pertains specifically to Laos and academic studies conducted on such data up to the present. In regards to the availability of spatial economic data, efforts have been made to identify not only data that has been made available as geographic information systems (GIS) data, but also those with sufficient place labels attached. The rest of the report is organized as follows. Section 2 reviews the maps available for Laos, both in hard copy and editable electronic formats. Section 3 summarizes the spatial economic data available for Laos at the present time, and Section 4 reviews and categorizes the many economic studies utilizing these spatial data. Section 5 give examples of some of the spatial industrial data collected for this research. Section 6 provides a summary of the findings and gives some indication of the direction of the final report due for completion in fiscal 2010.

An analog model for global macro investing

This study proposes a systematic model that is able to fit the Global Macro Investing universe. The Analog Model tests the possibility of capturing the likelihood of an optimal investment allocation based on similarity across different periods in history. Instead of observing Macroeconomic data, the model uses financial markets’ variables to classify unknown short-term regimes. This methodology is particularly relevant considering that asset classes and investment strategies react differently to specific macro environment shifts.

Forecasting with Medium and Large Bayesian VARs

This paper is motivated by the recent interest in the use of Bayesian VARs for forecasting, even in cases where the number of dependent variables is large. In such cases, factor methods have been traditionally used but recent work using a particular prior suggests that Bayesian VAR methods can forecast better. In this paper, we consider a range of alternative priors which have been used with small VARs, discuss the issues which arise when they are used with medium and large VARs and examine their forecast performance using a US macroeconomic data set containing 168 variables. We nd that Bayesian VARs do tend to forecast better than factor methods and provide an extensive comparison of the strengths and weaknesses of various approaches. Our empirical results show the importance of using forecast metrics which use the entire predictive density, instead of using only point forecasts.

Reconsideration of dimensions and curve fitting practice in economics ellaborating on Georgescu-Roegen’s economic methodology

This paper is to examine the proper use of dimensions and curve fitting practices elaborating on Georgescu-Roegen’s economic methodology in relation to the three main concerns of his epistemological orientation. Section 2 introduces two critical issues in relation to dimensions and curve fitting practices in economics in view of Georgescu-Roegen’s economic methodology. Section 3 deals with the logarithmic function (ln z) and shows that z must be a dimensionless pure number, otherwise it is nonsensical. Several unfortunate examples of this analytical error are presented including macroeconomic data analysis conducted by a representative figure in this field. Section 4 deals with the standard Cobb-Douglas function. It is shown that the operational meaning cannot be obtained for capital or labor within the Cobb-Douglas function. Section 4 also deals with economists "curve fitting fetishism". Section 5 concludes thispaper with several epistemological issues in relation to dimensions and curve fitting practices in economics.

Euroland: besser als befürchtet aber schlechter als erhofft?

Die Schaffung der Europäischen Währungsunion hatte in wissenschaftlichen Kreisen heftigste Kontroversen ausgelöst. Der vorliegende Beitrag unternimmt, dreieinhalb Jahre nach dem Beginn der Währungsunion, eine Bestandsaufnahme der Entwicklungen in den diesbezüglich zugrundeliegenden zentralen Problembereichen: den Arbeitsmärkten, der Inflationsentwicklung und der Budgetproblematik. Eine Analyse der Thesen im Lichte der bisherigen makroökonomischen Daten führt zu einem gemischten Urteil: während die Entwicklungen auf den Arbeitsmärkten und im Inflationsbereeich bislang in der Tendenz positiv sind, stagniert die angestrebte Besserung bei der Budget- und Schuldenproblematik. Da die weltwirtschaftlichen Einflüsse bislang günstig bzw. für alle Teilnehmerländer von ähnlicher Wirkung waren, steht ein harter Test des makroökonomischen Rahmens aber noch aus.

Plan exportador Asquim E.A.T.

El desarrollo de un plan exportador se realiza en diferentes etapas y al tener la información de cada una de estas, será más fácil seguir paso a paso el proceso. Inicialmente se debe saber como se encuentra la empresa y esta debe determinar que producto es el que se puede llegar a exportar, este debe cumplir ciertas características como ventas nacionales altas, ser innovador, tener una ficha técnica, etc., al tener claro el producto se debe buscar la partida arancelaria del mismo, teniendo esta se realiza un estudio y un seguimiento de la partida arancelaria en los últimos años en Colombia, así se conocerá el comportamiento de esta partida arancelaria, tanto en sus importaciones como exportaciones. Partiendo de este producto estrella se entra en una segunda fase y es la de buscar mercados internacionales que sean posibles compradores, esta fase es llamada Inteligencia de Mercados. En esta fase se tienen en cuenta diferentes factores de cada país como los indicadores socioeconómicos, principales ciudades, el tipo de moneda que manejan, datos macroeconómicos, tratamiento arancelario, precio internacional, entre otros; de esta fase salen tres mercados claves y son países los cuales podrán comprar el producto en un futuro, el primer mercado es el objetivo, el segundo es el alterno y en ultimo lugar será el contingente. Al tener los tres mercados se debe saber a que precio se venderá el producto en el exterior, la inteligencia de mercados da precios aproximados, pero la empresa debe hacer un análisis de sus costos y debe entrar a averiguar por medio de las SIAS o agentes aduaneros (intermediarios que ayudan en los procesos de exportación de los producto) cuanto seria lo que se cobraría por la exportación por medio de ellos y de esta manera se calculara un precio, así la empresa conocerá si es competitiva o no a nivel internacional. Después de esta fase la empresa buscara estrategias de mejoramiento para su producto, precio, plaza y promoción, las conocidas 4Ps, este análisis se realiza para cada mercado. Además se realiza un análisis DOFA donde la empresa se analiza internamente en sus aéreas de mercadeo, organizacional, finanzas y producción. Todas estas fases se deben realizar detalladamente para lograr un exitoso plan exportador. Para las PYMES colombianas contar con un plan exportador es algo muy importante y valioso, es un aprendizaje donde las empresas aprenden a tener una visión internacional. ASQUIM E.A.T. es una PYME que conoció y aprendió como seria el mundo internacional, además el plan exportador le ayudo a plantear mecanismos de mejoramiento, los cuales realiza actualmente para en un futuro lograr ser mas competitivo.

Gradients of the intergenerational transmission of health in developing countries

This paper investigates sensitivity of the intergenerational transmission of health to changes in the socioeconomic and public health environment into which children are born using individual survey data on 2.24 million children born to 600000 mothers during 1970-2000 in 38 developing countries merged by country and cohort with macroeconomic data. We find that children are more likely to bear the penalty exerted by poor maternal health if they are conceived or born in adverse socioeconomic conditions. Equivalently, shocks to the child’s birth environment are more damaging of children born to women with a weaker stock of health at birth.

On SETAR non-linearity and forecasting

We compare linear autoregressive (AR) models and self-exciting threshold autoregressive (SETAR) models in terms of their point forecast performance, and their ability to characterize the uncertainty surrounding those forecasts, i.e. interval or density forecasts. A two-regime SETAR process is used as the data-generating process in an extensive set of Monte Carlo simulations, and we consider the discriminatory power of recently developed methods of forecast evaluation for different degrees of non-linearity. We find that the interval and density evaluation methods are unlikely to show the linear model to be deficient on samples of the size typical for macroeconomic data

Forecasting with Vector Nonlinear Time Series Models

This work concerns forecasting with vector nonlinear time series models when errorsare correlated. Point forecasts are numerically obtained using bootstrap methods andillustrated by two examples. Evaluation concentrates on studying forecast equality andencompassing. Nonlinear impulse responses are further considered and graphically sum-marized by highest density region. Finally, two macroeconomic data sets are used toillustrate our work. The forecasts from linear or nonlinear model could contribute usefulinformation absent in the forecasts form the other model.

Common Features in Vector Nonlinear Time Series Models

This thesis consists of four manuscripts in the area of nonlinear time series econometrics on topics of testing, modeling and forecasting nonlinear common features. The aim of this thesis is to develop new econometric contributions for hypothesis testing and forecasting in these area. Both stationary and nonstationary time series are concerned. A definition of common features is proposed in an appropriate way to each class. Based on the definition, a vector nonlinear time series model with common features is set up for testing for common features. The proposed models are available for forecasting as well after being well specified. The first paper addresses a testing procedure on nonstationary time series. A class of nonlinear cointegration, smooth-transition (ST) cointegration, is examined. The ST cointegration nests the previously developed linear and threshold cointegration. An Ftypetest for examining the ST cointegration is derived when stationary transition variables are imposed rather than nonstationary variables. Later ones drive the test standard, while the former ones make the test nonstandard. This has important implications for empirical work. It is crucial to distinguish between the cases with stationary and nonstationary transition variables so that the correct test can be used. The second and the fourth papers develop testing approaches for stationary time series. In particular, the vector ST autoregressive (VSTAR) model is extended to allow for common nonlinear features (CNFs). These two papers propose a modeling procedure and derive tests for the presence of CNFs. Including model specification using the testing contributions above, the third paper considers forecasting with vector nonlinear time series models and extends the procedures available for univariate nonlinear models. The VSTAR model with CNFs and the ST cointegration model in the previous papers are exemplified in detail,and thereafter illustrated within two corresponding macroeconomic data sets.

A importância de um índice de volatilidade para o mercado brasileiro

Este trabalho objetiva analisar a importância de um índice de volatilidade implícita para o mercado brasileiro. Por ser conhecida como uma medida das expectativas futuras dos investidores, diversos estudos, principalmente na literatura estrangeira, tem consegui extrair importantes informações quanto às mudanças na volatilidade implícita com a chegada de novos dados sobre a economia. Analisando as opções de juros (IDI) e de dólar, este trabalho verifica que informações de dados macroeconômicos impactam a volatilidade. Os resultados demonstram que as expectativas quanto ao mercado de juros são impactadas por diversos dados, porém o mesmo não acontece com o mercado de dólar, a qual se demonstrou ser impactada somente por intervenções do Banco Central via colocação de swaps. Por fim, o trabalho conclui que existem varáveis não transacionáveis que explicam as variações na volatilidade implícita, mostrando que as volatilidades implícitas das opções possuem bastantes informações quanto às expectativas.

Estudo comparativo do poder preditivo do PIB brasileiro por variáveis macroeconômicas em relação ao conjunto de variáveis da estrutura de taxa de juros

O trabalho busca comparar dois conjuntos de informações para a projeção das variações do PIB brasileiro: através de modelos econométricos aplicados sobre a série univariada do PIB, e a aplicação dos mesmos modelos, mas contemplando adicionalmente o conjunto de informação com dados da estrutura a termo de taxa de juros de swap PRÉ-DI. O objetivo é verificar, assim como descrito na literatura internacional, se informações de variáveis financeiras tem a capacidade de incrementar o poder preditivo de projeções de variáveis macroeconômicas, na medida em que esses dados também embutem as expectativas dos agentes em relação ao desenvolvimento do cenário econômico. Adicionalmente, o mesmo procedimento aplicado para os dados brasileiros é aplicado sobre as informações dos Estados Unidos, buscando poder fornecer ao estudo uma base de comparação sobre os dados, tamanho da amostra e estágio de maturidade das respectivas economias. Como conclusão do resultado do trabalho está o fato de que foi possível obter um modelo no qual a inclusão do componente de mercado apresenta menores erros de projeção do que as projeções apenas univariadas, no entanto, os ganhos de projeção não demonstram grande vantagem comparativa a ponto de poder capturar o efeito de antecipação do mercado em relação ao indicador econômico como em alguns casos norte-americanos. Adicionalmente o estudo demonstra que para este trabalho e amostra de dados, mesmo diante de diferentes modelos econométricos de previsão, as projeções univariadas apresentaram resultados similares.