The finance-growth nexus: The role of banks

We contribute to the finance-growth nexus literature by showing that credit origin, bank ownership, type of credit, and bank type matter in economic growth. We use a unique dataset covering 5555 cities in Brazil, with granular information on credit characteristics. We find that non-earmarked credit to the corporate sector is associated with municipal economic growth more strongly than earmarked credit, despite the increase in the relevance of the latter after the global financial crisis. We also find that the type of credit—whether the loans are general purpose or for a specific purpose—is associated with economic growth in different ways. Overall, credit provided to the corporate sector by domestic private banks is correlated with higher economic growth rates. In contrast, the relationship between credit from state-owned banks and economic growth becomes statistically significant only after the crisis. Although we follow the finance-growth literature in our empirical exercises using internal instruments in generalized method of moments (GMM) estimations, we also conduct robustness tests using two additional external instruments: the number of complaints filed against each bank and local credit accessibility. Our findings with external instruments are the same with respect to the use of traditional internal instruments in GMM estimations.     

Comparison of Classical and Bayesian Approaches for Intervention Analysis

Intervention analysis has been recently the subject of several studies, mainly because real time series present a wide variety of phenomena that are caused by external and/or unexpected events. In this work, transfer functions are used to model different forms of intervention to the mean level of a time series. This is performed in the framework of state-space models. Two canonical forms of intervention are considered: pulse and step functions. Static and dynamic explanation of the intervention effects, normal and non-normal time series, detection of intervention, and study of the effect of outliers are also discussed. The performance of the two approaches is compared in terms of point and interval estimation through Monte Carlo simulation. The methodology was applied to real time series and showed satisfactory results for the intervention models used.     

The impossibility of effective enforcement mechanisms in collateralized credit markets

We analyze the possibility of the simultaneous presence of two key features in price-taking sequential economies: collateralized credit operations and effective additional enforcement mechanisms, i.e. those implying payments besides the value of collateral guarantees.     

Forecasting Brazilian inflation by its aggregate and disaggregated data: a test of predictive power by forecast horizon

This work aims to compare the forecast efficiency of different types of methodologies applied to Brazilian consumer inflation (Índice de Preços ao Consumidor Amplo; IPCA). We will compare forecasting models using disaggregated and aggregated data from IPCA over 12 months ahead. We used IPCA in a monthly basis, over the period between January 1996 and March 2012. Out-of-sample analysis will be made through the period of January 2008 to March 2012. The disaggregated models were estimated by Seasonal Autoregressive Integrated Moving Average (SARIMA) and will have different levels of disaggregation from IPCA as groups and items, as well as disaggregation with more economic sense used by Brazilian Central Bank as: (1) services, monitored prices, food and industrials and (2) durables, non-durables, semi-durables, services and monitored prices. Aggregated models will be estimated by time series techniques as SARIMA, state-space structural models and Markov-switching. The forecasting accuracy among models will be made by the selection model procedure known as Model Confidence Set developed by Peter Hansen, Asger Lunde and James Nason. We were able to find evidence of forecast accuracy gains in models using more disaggregated rather than aggregate data.     

Macroeconomic Determinants of Investment under Inflation Targeting: Empirical Evidence from the Brazilian Economy

The use of interest rate as the main tool by which central banks implement inflation targets points to a strong link between private investment decisions and monetary policy. With the objective of contributing to the literature surrounding macroeconomic determinants of investment under inflation targeting, an empirical analysis through Generalized Method of Moments models for the Brazilian case is made. In a general way, the findings underscore the relevance of macroeconomic variables for the determination of investment. In particular, we find that success inflation targeting creates a stable macroeconomic environment that promotes private investment.     

Financing choice and local economic growth: evidence from Brazil

Journal of Economic Growth - We study how financing non-traditional local activities, conceived here as a proxy for activity diversification, is associated with economic growth. We use...     

U.S. R&D internationalization in less‐developed countries: Determinants and insights from Brazil,China, and India

The growing U.S. R&D internationalization has historically been concentrated in developed countries. However, in the past few decades, the internationalization has moved toward less‐developed countries (LDCs), particularly Brazil, China, and India. What location factors are making some LDCs more “inviting” for U.S. R&D offshore? To answer this first question, we constructed a panel data using secondary data from the U.S. Bureau of Economic Analysis regarding the R&D investment made by the majority‐owned foreign affiliates of U.S. parent companies in 71 countries. We then applied a Heckman two‐step correction for selection bias test. The results highlight some important differences between developed countries’ and LDCs’ attractiveness. Based on these initial results, we conducted a detailed analysis of the determinants of U.S. R&D investments in Brazil, China, and India, which revealed that China’s determinants mostly match those found in more developed countries.     

Empirical evidence of the existence of speculative bubbles in the prices of stocks traded on the São Paulo Stock Exchange

Speculative price bubbles are defined as a significant deviation between an asset's intrinsic value and its market value and in this paper it refers to stock values. Literature about the theme has noted the existence of bubbles in various types of markets and their respective assets. A great deal of effort has been directed toward identifying bubbles in stock price indices. However, few research endeavors focus on assets as the unit of analysis. Studies about stocks in Brazil have identified the presence of bubbles in IBOVESPA (São Paulo Stock Exchange Index). Given this context and assuming that the speculative bubbles are present in the Brazilian stock market, this research is focused on the following question: Is there evidence of the existence of speculative bubbles in stock prices traded on the São Paulo Stock Exchange? Econometric tests were performed on twenty-seven stocks, based upon their positions each semester, for the period between the first semesters of 1990 until the first semester of 2010. The nominal values of the selected stocks were adjusted for inflation by the IPCA (Brazilian Consumer Price Index). In order to identify the presence of bubbles, we applied the Johansen non-cointegration test and/or the Granger non-causality test between the intrinsic value, dividends and interest on equity capital, and the market value (semester closing price) of the stocks. The primary findings reveal a presence of bubbles in twenty of the twenty-seven stocks, at a 5% significance level. Of the seven stocks not showing evidence of bubbles, six are financial institutions. In five stocks the tests reveal Granger causality stemming from the market value toward the intrinsic value. The study findings are consistent and contribute with previous research in the literature and, are useful for investors, financial institutions, academics, government agents, and traders.