Did PROGRESA send drop-outs back to school?

This paper analyzes the effect of PROGRESA education grants on school enrollment. It looks at its effect on total school enrollment and in particular on school enrollment of drop-outs, i.e. those children who face a re-enrollment decision since they were not enrolled in school the year prior to the implementation of the PROGRESA program. Estimates of the impact of PROGRESA education grants on drop-outs and non-drop-outs are obtained applying difference estimation and maximum likelihood estimation of a reduced form equation for schooling decision. Differences in results between both groups of children are discussed looking at the distribution of marginal effects. PROGRESA did send drop-outs back to school. It had a larger effect on drop-outs than on non-drop-outs. However, for the particular group of girls who dropped out of school just before attending secondary school PROGRESA grants only had a minor effect. This last finding highlights the fact that determinants of the schooling decision are different for young girls and that PROGRESA grants do not provide a strong enough incentive to send them back to school

Pricing and Marketing Rules with Brand Loyalty

Many firms face a dynamic trade-off: if price is reduced, the firm attracts new customers who will yield profits in the future, but it also forgoes the opportunity to squeeze profits now from loyal customers. This paper identifies a rule that represents the optimal resolution of this trade-off, in terms of an intuitive modification to the static Lerner rule. We find that the “effective” price elasticity depends on the discount rate used by the firm, on the rate of depreciation of the clientele through exit from the stock of repeat purchasers, and on a weighted sum of the price elasticities of the flow of entries into the stock of repeat-purchasers and the flow of exits from the stock of repeat-purchasers. None of these factors enter the optimal pricing strategy for a firm facing a conventional demand function with instantaneous adjustment, i.e. where consumers are “fast switchers”, rather than repeat-purchasers. We also find optimal rules for marketing investment and for quality of service, which are extensions of the Dorfman-Steiner conditions. The paper shows that our rules, with suitable modifications, are valid for many market structures, including monopolistic competition, pure monopoly and strong cartels, dominant firms and oligopolists that have full commitment ability. In the case of dominant firms and oligopolists that cannot commit to their strategy paths, these simple optimal pricing and marketing rules do not apply.

A Theory of Noncontributory Pension Design

Noncontributory subsidies for the old poor (first-pillar pensions) affect the welfare of hundreds of millions around the world. Their benevolent rationale is to redistribute progressively, subject to efficiency considerations. This paper focuses on a critical efficiency issue: first pillars may affect another, even bigger program, namely contributory pensions for the middle classes, by inducing a reduction in the density of contributions. A major source of concern with contributory pensions in emerging economies is that the total replacement rate is too small for participants with low density, which are prevalent. The paper develops a model where density of contribution is endogenous, because for a substantial subset of jobs, the State is unable or unwilling to impose a mandate to contribute. Thus, the job selection decision is bundled with a saving decision. The first finding is that bundling modifies the effective rate of return on contributions, raising it without bound as earnings in uncovered jobs become smaller (relative to earnings in covered jobs). Another finding is that the standard designs of first-pillar pensions reduce the equilibrium density of contributions. Thus, standard first-pillar designs do crowd out contributory pensions for the middle classes. The paper then analyzes two second-generation designs. The “proportional” minimum pension is found to create horizontal inequity and inefficiency. In contrast, a subsidy with a small withdrawal rate applied to contributory pensions minimizes the loss of contribution density. Optimal income taxation theory suggests that the latter also provides the most efficient progressive redistribution.Social security, pensions, density

Discrete Fourier Transform Improves the Prediction of the Electronic Properties of Molecules in Quantum Machine Learning

High-throughput approximations of quantum mechanics calculations and combinatorial experiments have been traditionally used to reduce the search space of possible molecules, drugs and materials. However, the interplay of structural and chemical degrees of freedom introduces enormous complexity, which the current state-of-the-art tools are not yet designed to handle. The availability of large molecular databases generated by quantum mechanics (QM) computations using first principles open new venues for data science to accelerate the discovery of new compounds. In recent years, models that combine QM with machine learning (ML) known as QM/ML models have been successful at delivering the accuracy of QM at the speed of ML. The goals are to develop a framework that will accelerate the extraction of knowledge and to get insights from quantitative process-structure-property-performance relationships hidden in materials data via a better search of the chemical compound space, and to infer new materials with targeted properties. In this study, we show that by integrating well-known signal processing techniques such as discrete Fourier transform in the QM/ML pipeline, the outcomes can be significantly improved in some cases. We also show that the spectrogram of a molecule may represent an interesting molecular visualization tool.Comment: 4 pages, 3 figures, 2 tables. Accepted to present at 32nd IEEE Canadian Conference in Electrical Engineering and Computer Scienc

Nonfractional Memory: Filtering, Antipersistence, and Forecasting

The fractional difference operator remains to be the most popular mechanism to generate long memory due to the existence of efficient algorithms for their simulation and forecasting. Nonetheless, there is no theoretical argument linking the fractional difference operator with the presence of long memory in real data. In this regard, one of the most predominant theoretical explanations for the presence of long memory is cross-sectional aggregation of persistent micro units. Yet, the type of processes obtained by cross-sectional aggregation differs from the one due to fractional differencing. Thus, this paper develops fast algorithms to generate and forecast long memory by cross-sectional aggregation. Moreover, it is shown that the antipersistent phenomenon that arises for negative degrees of memory in the fractional difference literature is not present for cross-sectionally aggregated processes. Pointedly, while the autocorrelations for the fractional difference operator are negative for negative degrees of memory by construction, this restriction does not apply to the cross-sectional aggregated scheme. We show that this has implications for long memory tests in the frequency domain, which will be misspecified for cross-sectionally aggregated processes with negative degrees of memory. Finally, we assess the forecast performance of high-order $AR$ and $ARFIMA$ models when the long memory series are generated by cross-sectional aggregation. Our results are of interest to practitioners developing forecasts of long memory variables like inflation, volatility, and climate data, where aggregation may be the source of long memory

The school reentry decision on poor girls: structural estimation and policy analysis using PROGRESA database

In this paper I present a dynamic structural model of girls' schooling choices and estimate it using the Mexican PROGRESA database. This structural approach allows evaluating the efectiveness of several policies to increase school reentry rates for girls in low-income households. To increase school attendance among poor children in developing countries, policy makers have implemented conditional cash transfers programs. Although transfers have been successful in keeping girls at school, they do not increase school attendance among girls who have dropped out of school. Cash transfer programs may fail because most of these poor girls leave school to stay at home helping in housework, rather than working for a salary. Results suggest that effective policies to increase school reentry rates for poor girls are free access to community nurseries and kindergartens, and increasingg the availability of secondary schools.Policy evaluation, Dynamic discrete choice structural models, School choices for girls, School reentry, PROGRESA

The 2008 Chilean Reform to First-Pillar Pensions

Chile approved in early 2008 the replacement of her two current non-contributory subsidies for the old poor for a unified program with a pioneering design, with phase-in ending in 2012. This paper describes the political economy of this reform and evaluates it with regards to efficiency and equity. The design is analogous to one adopted in Finland in 1957, with two differences: First, the subsidy withdrawal rate in response to the individual’s contributory pension benefit is lower, about 30% rather than 50%. Second, preserving a tradition introduced in 1975, benefits are also withdrawn in response to per capita household income.social security, welfare programs, political economy of reform