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Conventional wisdom predicts that changes in macroeconomic conditions significantly affect income inequality. In this paper, we hypothesize that the way in which macroeconomic conditions affect inequality depends on how these conditions influence the constituents of total inequality: inequality of opportunity (IO) and inequality of effort (IE). Using the PSID database for the United States (1970–2009), we first decompose total inequality into these components. Then, we specify a dynamic model that relates each inequality component to a set of macroeconomic factors. Apart from real GDP and inflation rates, the most widely used factors in the literature, we also consider outstanding consumer credits and public welfare and health care expenditures. We find that real GDP and outstanding credits have a negative and significant effect upon IO and IE, while inflation has a positive and significant effect only on IE, and welfare expenditures have a negative and significant effect only on IO.

Traditionally, loan officers use different credit scoring models to complement judgmental methods to classify consumer loan applications. This study explores the use of decision trees, AdaBoost, and support vector machines (SVMs) to identify potential bad loans. Our results show that AdaBoost does provide an improvement over simple decision trees as well as SVM models in predicting good credit clients and bad credit clients. To cross-validate our results, we use k-fold classification methodology.

I find that median wealth plummeted over the years 2007–2010, and by 2010 was at its lowest level since 1969. The inequality of net worth, after almost two decades of little movement, was up sharply from 2007 to 2010. Relative indebtedness continued to expand from 2007 to 2010, particularly for the middle class, though the proximate causes were declining net worth and income rather than an increase in absolute indebtedness. In fact, the average debt of the middle class actually fell in real terms by 25 percent. The sharp fall in median wealth and the rise in inequality in the late 2000s are traceable to the high leverage of middle-class families in 2007 and the high share of homes in their portfolio. The racial and ethnic disparity in wealth holdings, after remaining more or less stable from 1983 to 2007, widened considerably between 2007 and 2010. Hispanics, in particular, got hammered by the Great Recession in terms of net worth and net equity in their homes. Households under age 45 also got pummeled by the Great Recession, as their relative and absolute wealth declined sharply from 2007 to 2010.

We address the problem of selecting the common factors that are relevant for forecasting macroeconomic variables. In economic forecasting using diffusion indexes, the factors are ordered, according to their importance, in terms of relative variability, and are the same for each variable to predict, that is, the process of selecting the factors is not supervised by the predictand. We propose a simple and operational supervised method, based on selecting the factors on the basis of their significance in the regression of the predictand on the predictors. Given a potentially large number of predictors, we consider linear transformations obtained by principal components analysis. The orthogonality of the components implies that the standard t-statistics for the inclusion of a particular component are independent, and thus applying a selection procedure that takes into account the multiplicity of the hypotheses tests is both correct and computationally feasible. We focus on three main multiple testing procedures: Holm's sequential method, controlling the familywise error rate, the Benjamini–Hochberg method, controlling the false discovery rate, and a procedure for incorporating prior information on the ordering of the components, based on weighting the p-values according to the eigenvalues associated to the components. We compare the empirical performances of these methods with the classical diffusion index (DI) approach proposed by Stock and Watson, conducting a pseudo-real-time forecasting exercise, assessing the predictions of eight macroeconomic variables using factors extracted from an U.S. dataset consisting of 121 quarterly time series. The overall conclusion is that nature is tricky, but essentially benign: the information that is relevant for prediction is effectively condensed by the first few factors. However, variable selection, leading to exclude some of the low-order principal components, can lead to a sizable improvement in forecasting in specific cases. Only in one instance, real personal income, we were able to detect a significant contribution from high-order components.

This paper shows that the parsimoniously time-varying methodology of Callot and Kristensen (2015) can be applied to factor models. We apply this method to study macroeconomic instability in the United States from 1959:1 to 2006:4 with a particular focus on the Great Moderation. Models with parsimoniously time-varying parameters are models with an unknown number of break points at unknown locations. The parameters are assumed to follow a random walk with a positive probability that an increment is exactly equal to zero so that the parameters do not vary at every point in time. The vector of increments, which is high dimensional by construction and sparse by assumption, is estimated using the Lasso. We apply this method to the estimation of static factor models and factor-augmented autoregressions using a set of 190 quarterly observations of 144 US macroeconomic series from Stock and Watson (2009). We find that the parameters of both models exhibit a higher degree of instability in the period from 1970:1 to 1984:4 relative to the following 15 years. In our setting the Great Moderation appears as the gradual ending of a period of high structural instability that took place in the 1970s and early 1980s.

Financial systemic risk is often assessed by the interconnectedness of financial institutes (FI) in terms of cross-ownership, overlapping investment portfolios, interbank credit exposures, etc. Less is known about the interconnectedness between FIs through the lens of consumer credits. Using detailed consumer credit data in Canada, this chapter constructs a novel banking network to measure FIs’ interconnectedness in the consumer credit markets. Results show that FIs on average are more connected to each other over the sample period, with the interconnectedness measure increases by 19% from 2013 Q4 to 2019 Q4. FIs with more diversified portfolios are more connected in the network. Among various types of FIs, secondary FIs have the notable increase in interconnectedness. Domestic Systemically Important Banks and secondary FIs offering a broad range of loan products are more connected to large FIs, while those specialized in single loan types are more connected to their industry peers. FI connectedness is also significantly related to their participation in the mortgage markets.

Hisbah is one of the distinguished institutions that had emerged since the early days of the Islamic empire. Based on its cardinal duty to enjoin good and prohibit evil, over time, its functions gradually expanded, and its responsibilities increasingly grew. In light of the contemporary trend in establishing institutional framework for consumer protection, entrusting an agency with multifarious tasks may not be the best and effective way in handling consumer protection issues. Thus, this chapter attempts to explore the new paradigm of hisbah as a consumer protection institution in Malaysia with a special reference to the Islamic consumer credit industry. While utilising the doctrinal legal research methodology, relevant sources of law have been examined and analysed. This research finds that the classical hisbah institution provides a good reference point in establishing regulatory agency and dispute management body. Nevertheless, some modifications are required to remain relevant especially in terms of specialisation of role and function. Likewise, it is viewed that adjustment of the hisbah institution is also necessary regarding the characteristic of the muhtasib (ombudsman).

This paper examines the role of structured products in the 2008–2009 financial crisis. The growth of asset securitization has allowed loans that used to be funded by traditional intermediaries, including commercial banks, to be funded in securities markets. As credit-related services became unbundled, layers of transactions were added to the financial intermediation process. These layers were added as structured products, e.g., credit default swaps, in the over-the-counter market. This paper looks at the evolution of credit markets and the importance of using off-balance-sheet-based measures as an alternative in assessing the financial sector.

The Bureau of Economics in the Federal Trade Commission has a three-part role in the Agency and the strength of its functions changed over time depending on the preferences and ideology of the FTC’s leaders, developments in the field of economics, and the tenor of the times. The over-riding current role is to provide well considered, unbiased economic advice regarding antitrust and consumer protection law enforcement cases to the legal staff and the Commission. The second role, which long ago was primary, is to provide reports on investigations of various industries to the public and public officials. This role was more recently called research or “policy R&D”. A third role is to advocate for competition and markets both domestically and internationally. As a practical matter, the provision of economic advice to the FTC and to the legal staff has required that the economists wear “two hats,” helping the legal staff investigate cases and provide evidence to support law enforcement cases while also providing advice to the legal bureaus and to the Commission on which cases to pursue (thus providing “a second set of eyes” to evaluate cases). There is sometimes a tension in those functions because building a case is not the same as evaluating a case. Economists and the Bureau of Economics have provided such services to the FTC for over 100 years proving that a sub-organization can survive while playing roles that sometimes conflict. Such a life is not, however, always easy or fun.