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.     

From private label to co-branded credit card: an assessment of the impact of a change in value proposition over customer value perception and company value capture

Journal of Financial Services Marketing - Purpose: The aim of this paper is to evaluate the success of a value proposition over time, considering two aspects: customer’s perceived value and...     

Speed under sail during the early industrial revolution (c. 1750–1830)

This article measures technological progress in oceanic shipping directly by using a large database of daily log entries from British, Dutch, and Spanish ships to estimate daily sailing speed in different wind conditions from 1750 to 1850. Against the consensus among economic (but not maritime) historians that the technology of sailing ships was fairly static during this time, we find that average sailing speeds of British East India Company and Navy ships in moderate to strong winds rose considerably after the 1770s. Driving this progress was the introduction of coppering in the 1780s, but subsequent rises are probably due to a continuous evolution of sails and rigging, and improved hulls that allowed a greater area of sail to be set safely in a given wind. By contrast, the speeds of Dutch and Spanish vessels were stagnant. Using separate data on the crossing times of Atlantic mail packets, we find gradual progress from the 1750s, followed by marked improvements when American packets appeared in the 1820s.     

IF WE CONFESS OUR SINS

I consider a scenario where a social planner suspects that a crime has been committed. There are many suspects and at most one of them is guilty. I characterize the optimal mechanism for the social planner under different assumptions with respect to her commitment power. I find that the optimal mechanism is a “confession inducing mechanism”: Before an investigation, each agent can confess to being guilty in exchange for a reduced punishment. I find that these mechanisms do better than the traditional trial mechanism because of information externalities: When an agent credibly confesses his guilt, he reveals everyone else's innocence.     

Forecasting UK consumer price inflation using inflation forecasts

The inflation rate is a key economic indicator for which forecasters are constantly seeking to improve the accuracy of predictions, so as to enable better macroeconomic decision making. Presented in this paper is a novel approach which seeks to exploit auxiliary information contained within inflation forecasts for developing a new and improved forecast for inflation by modeling with Multivariate Singular Spectrum Analysis (MSSA). Unlike other forecast combination techniques, the key feature of the proposed approach is its use of forecasts, i.e. data into the future, within the modeling process and extracting auxiliary information for generating a new and improved forecast. We consider real data on consumer price inflation in UK, obtained via the Office for National Statistics. A variety of parametric and nonparametric models are then used to generate univariate forecasts of inflation. Thereafter, the best univariate forecast is considered as auxiliary information within the MSSA model alongside historical data for UK consumer price inflation, and a new multivariate forecast is generated. We find compelling evidence which shows the benefits of the proposed approach at generating more accurate medium to long term inflation forecasts for UK in relation to the competing models. Finally, through the discussion, we also consider Google Trends forecasts for inflation within the proposed framework.     

Dynamic managerial capabilities: Scale development and validation

Studies on dynamic managerial capabilities still have a rather theoretical nature, and there is great difficulty in finding a valid, reliable instrument to measure this construct. The present study contributes to solving this problem: It aims to develop and validate a scale to measure dynamic managerial capabilities. In this investigation, we develop a scale for three factors related to dynamic managerial capabilities: human capital, managerial cognition (already described in the literature), and relationship networks. The prominent finding in this research is the factor that is referred to here as relationship networks.     

Stock Market Reaction to Monetary Policy: An Event Study Analysis of the Brazilian Case

This article examines the relationship between the monetary policy implemented by the Central Bank of Brazil and the stock market. We implement event study analysis and analyze the effect of the anticipated and unanticipated components of monetary policy decisions on the returns of the IBOVESPA index and 53 stocks. We find that monetary policy has a significant effect on the stock market, but is only responsible for a small proportion of market variation. The analysis at the sector level with expected returns identifies that the financial sector is the most affected by this policy, whereas with excess returns only industrial goods are significantly affected. Moreover, individual assets respond in a rather heterogeneous fashion to monetary policy; however, when we look at excess returns, we identify a reduction in the intensity and in the number of companies impacted by monetary policy. Finally, the monetary shock is explained by unanticipated variations in the unemployment rate, in the Industrial Production Index, in the General Market Price Index, and in the Broad Consumer Price Index.     

Examining the predictive validity of SUS-TAS with maximum parsimony in developing island countries

The Sustainable Tourism Attitude Scale (SUS-TAS) has been used as a tool to gauge the sentiment of local residents toward sustainable tourism development. This scale has been validated in cross-cultural settings by several scholars. In a like manner, in order to validate this scale, data were collected in the Cape Verde islands (off the coast of Africa) and the results showed (1) a parsimonious version of the 21-item SUS-TAS that facilitates the process of data collection without compromising its robustness and psychometric properties, (2) a validated second-order factor model, confirming that the seven factors of SUS-TAS can be loaded in two broader dimensions named “perceived tourism impacts” and “expected tourism sustainability”, (3) a SUS-TAS second-order factor model with validity in predicting residents’ support for sustainable tourism development, (4) that SUS-TAS can be interpreted by seven individual factors and/or as a global factor as indicated by the hierarchical measurement model and predictive validity. Methodological and theoretical interpretations are discussed and future refinement and applications are also offered.     

Prepurchase financing pool: Revealing the IRR problem

Internal rate of return (IRR) is one of the most common and important indicators in investment analysis because it is often used by managers and practitioners as a decision-making criterion. Moreover, the IRR reflects the financial cost in financing decisions and it helps to answer the following question when comparing different financing alternatives: “Which loan is the cheapest?” Among the different types of loans in Brazil, there is a financial product called a prepurchase financing pool (PPFP) that is generally regarded as the best option for financing or loans. The objective of this article is to use the prepurchase financing pool to show the flaws of IRR in financial analysis. In particular, when IRR is used to evaluate the prepurchase financing pool, one finds problems of reliability regarding (i) existence, (ii) uniqueness, and (iii) economic interpretation of the rate. The results show that the prepurchase financing pool is relevant evidence that the IRR flaws are found in financial products.