Convergence Hypotheses are Ill-Posed:Non-stationarity of Cross-Country Income Distribution D

The recent literature on “convergence� of cross-country per capita incomes has been dominated by two competing hypotheses: “global convergence� and “club-convergence�. This debate has recently relied on the study of limiting distributions of estimated income distribution dynamics. Utilizing new measures of “stochastic stability�, we establish two stylized facts that question the fruitfulness of the literature’s focus on asymptotic income distributions. The first stylized fact is non-stationarity of transition dynamics, in the sense of changing transition kernels, which renders all “convergence� hypotheses that make long-term predictions on income distribution, based on relatively short time series, less meaningful. The second stylized fact is the periodic emergence, disappearance, and re-emergence of a “stochastically stable� middle-income group. We show that the probability of escaping a low-income poverty-trap depends on the existence of such a stable middle income group. While this does not answer the perennial questions about long-term effects of globalization on the cross-country income distribution, it does shed some light on the types of environments that are conducive to narrowing/global income distribution; convergence clubs; transition kernel; stochastic stability

Interest and the Paradox of Contemporary Islamic Law and Finance

In Sections 1 and 2, the article shall provide a brief introduction to various notions of Islamic law as they exist today, as well as the common-law nature of Islamic jurisprudence to establish the possibility of finding a compromise that renders minor modifications of the existing juristic positions coherent. In Sections 3 and 4, the article will provide translations of the entire Azhar Islamic Research Institute (IRI) fatwa, and large excerpts from the Council of the Islamic Jurisprudence Academy\u27s (IJA) rebuttal together with discussions of the juristic backgrounds of each opinion. In Section 5, the author will discuss the ideological roots of contemporary Islamic finance, which continue to shape Muslim views, both for jurists and lay people, regarding interest and permissible profit. In Section 6, the author will provide a brief survey of the most prominent Islamic financial instruments, illustrating the incoherence of juristic views that denounce “interest” and yet maintain that Islamic finance is “interest-free.” Lastly, the author will conclude by proposing a possible compromise between the two extreme views espoused by the IRI fatwa and the IJA rebuttal, which would allow for a coherent juristic and financial nexus in Islamic finance

A Consistent Test of Stationary Ergodicity

A formal statistical test of stationary-ergodicity is developed for known Markovian processes on R^d. This makes it applicable to testing models and algorithms, as well as estimated time series processes ignoring the estimation error. The analysis is conducted by examining the asymptotic properties of the Markov operator on density space generated by the transition in the state space. The test is developed under the null of stationary-ergodicity, and it is shown to be consistent against the alternative of nonstationary-ergodicity. The test can be easily performed using any of a number of standard statistical and mathematical computer packages

Oil Demand, Supply, andMedium-Term Price Prospects:A Wavelets-Based Analysis

The global “great recession” was precipitated in part by record high prices of oil and other commodities. Previous severe recessions have typically resulted in significantly lower energy prices, which in turn spurred growth and fueled a healthy recovery. In part due to expansionary monetary policies worldwide, oil prices have remained relatively high, making it difficult for the global economy to stage a strong recovery. The result is a short-to-medium term forecast of weak to modest growth, which – combined with continuously falling energyintensity of GDP – means that oil demand will remain stagnant or at best grow modestly. Under these circumstances, surging supply from U.S. shale and similar technologically-driven unconventional oil sources is likely to create excess supply and put strong downward pressure on oil prices. Voluntary reduction in oil production to prevent falling prices is highly unlikely, because swing producer Saudi Arabia and other GCC countries need revenues at the level of current volumes and prices in order to meet core budgetary requirements and prevent regime-change risk in the aftermath of “Arab Spring” revolts. Our wavelet analysis of all countries that have ever produced more than one million barrels of oil per day shows that regime change by itself would not result in significant reduction in oil production – although it may result in lower investment and therefore prevention of further increase in production capacity. However, war that destroys physical installations for the production and/or transport of oil can significantly disrupt oil supplies. In sum, if the outright war scenario is excluded, we expect prices to fall precipitously in the medium term (3-5 years). However, the continued threat of currently-contained civil wars into larger confrontations can maintain the current prices, especially if unprecedented monetary easing continues

Bayesian Economists...Bayesian Agents II: Evolution of Beliefs in the Single Sector Growth Model

In "Bayesian Economists ... Bayesian Agents I" (BBI), we generalized the results on Bayesian learning based on the martingale convergence theorem from the repeated to the sequential framework. In BBI, we showed that the variability introduced by the sequential framework is sufficient under very mild identifiability conditions to circumvent the incomplete learning results that characterize the literature. In this paper, we demonstrate that result in the neo-classical single sector growth model under even weaker identifiability conditions. We study the evolution of agent-beliefs in that model and show that, under reasonable conditions, the dependence of the current capital stock on the previous capital stock induces enough variability for our complete learning results to become relevant. Not only does complete learning take place from the subjective point of view of the agents' priors, but it also takes place from the point of view of an objective observer (modeling economist) who knows the true structure

Bayesian Economist ... Bayesian Agents I: An Alternative Approach to Optimal Learning

We study the framework of optimal decision making under uncertainty where the agents do not know the full structure of the model and try to learn it optimally. We generalize the results on Bayesian learning based on the martingale convergence theorem to the sequential framework instead of the repeated framework for which results are currently available. We also show that the variability introduced by the sequential framework is sufficient under very mild identifiability conditions to circumvent the incomplete learning results that characterize the literature. We then question the type of convergence so achieved, and give an alternative Bayesian approach whereby we let the economist himself be a Bayesian with a prior on the priors that his agents may have. We prove that such an economist cannot justify endowing all his agents with the same (much less the true) prior on the basis that the model has been running long enough that we can almost surely approximate any agent's beliefs by any other's. We then examine a possibly weaker justification based on the convergence of the economist's measure on beliefs, and fully characterize it by the Harris ergodicity of the relevant Markov kernel. By means of very simple examples, we then show that learning, partial learning, and non-learning may all occur under the weak conditions that we impose. For complicated models where the Harris ergodicity of the Markov kernel in question can neither be proved nor disproved, the mathematical/statistical test of Domowitz and El-Gamal (1989) can be utilized

A Consistent Test of Stationary Ergodicity

A formal statistical test of stationary-ergodicity is developed for known Markovian processes on R^d. This makes it applicable to testing models and algorithms, as well as estimated time series processes ignoring the estimation error. The analysis is conducted by examining the asymptotic properties of the Markov operator on density space generated by the transition in the state space. The test is developed under the null of stationary-ergodicity, and it is shown to be consistent against the alternative of nonstationary-ergodicity. The test can be easily performed using any of a number of standard statistical and mathematical computer packages