Estimating the Effect of the One-Child Policy on Sex Ratio Imbalance in China: Identification Based on the Difference-in-Differences

In China, the male-biased sex ratio has increased significantly. Because the one-child policy only applied to the Han Chinese but not to minorities, this unique affirmative policy allows us to identify the causal effect of the one-child policy on the increase in sex ratios by a difference-in-differences (DD) estimator. Using the 1990 census, we find that the strict enforcement of the one-child policy has led to 4.4 extra boys per 100 girls in the 1980s, accounting for about 94% of the total increase in sex ratios during this period. The robust tests indicate that the estimated policy effect is not likely confounded by other omitted policy shocks or socioeconomic changes. Moreover, we conduct the DD estimation using both the 2000 census and the 2005 mini-census. Our estimates suggest that the one-child policy has resulted in about 7.0 extra boys per 100 girls for the 1991-2005 birth cohort. The effect of the one-child policy accounts for about 57% and 54% of the total increases in sex ratios for the 1990s and the 2001-2005 birth cohorts, respectively.one-child policy, sex ratio imbalance, difference-in-differences estimator

The Effect of the One-Child Policy on Fertility in China: Identification Based on the Differences-in-Differences

This paper measures the effect of China's one-child policy on fertility by exploring the natural experiment that has been created by China's unique affirmative birth control policy, which is possibly the largest social experiment in human history. Because the one-child policy only applied to Han Chinese, but not to ethnic minorities, we construct a differences-in-differences estimator to identify the effect of the policy on fertility. Such a natural experiment is a rare opportunity, whether for the analysis of the effect on fertility or for the analysis of economics in general. Using two rounds of the Chinese Population Census, we find that the one-child policy has had a large effect on fertility. The average effect on the post-treatment cohorts on the probability of having a second child is as large as -11 percentage points. We also find that the magnitude is larger in urban areas and for more educated women. Our robustness tests suggest that our differences-in-differences estimates of the effect of the one-child policy are not very likely to be driven by other policy or socio-economic changes that have affected the Han and the minorities differently.

Two-Dimensional Pattern-Coupled Sparse Bayesian Learning via Generalized Approximate Message Passing

We consider the problem of recovering two-dimensional (2-D) block-sparse signals with \emph{unknown} cluster patterns. Two-dimensional block-sparse patterns arise naturally in many practical applications such as foreground detection and inverse synthetic aperture radar imaging. To exploit the block-sparse structure, we introduce a 2-D pattern-coupled hierarchical Gaussian prior model to characterize the statistical pattern dependencies among neighboring coefficients. Unlike the conventional hierarchical Gaussian prior model where each coefficient is associated independently with a unique hyperparameter, the pattern-coupled prior for each coefficient not only involves its own hyperparameter, but also its immediate neighboring hyperparameters. Thus the sparsity patterns of neighboring coefficients are related to each other and the hierarchical model has the potential to encourage 2-D structured-sparse solutions. An expectation-maximization (EM) strategy is employed to obtain the maximum a posterior (MAP) estimate of the hyperparameters, along with the posterior distribution of the sparse signal. In addition, the generalized approximate message passing (GAMP) algorithm is embedded into the EM framework to efficiently compute an approximation of the posterior distribution of hidden variables, which results in a significant reduction in computational complexity. Numerical results are provided to illustrate the effectiveness of the proposed algorithm

Multiscale examination of strain effects in Nd-Fe-B permanent magnets

We have performed a combined first-principles and micromagnetic study on the strain effects in Nd-Fe-B magnets. First-principles calculations on Nd2Fe14B reveal that the magnetocrystalline anisotropy (K) is insensitive to the deformation along c axis and the ab in-plane shrinkage is responsible for the K reduction. The predicted K is more sensitive to the lattice deformation than what the previous phenomenological model suggests. The biaxial and triaxial stress states have a greater impact on K. Negative K occurs in a much wider strain range in the ab biaxial stress state. Micromagnetic simulations of Nd-Fe-B magnets using first-principles results show that a 3-4% local strain in a 2-nm-wide region near the interface around the grain boundaries and triple junctions leads to a negative local K and thus decreases the coercivity by ~60%. The local ab biaxial stress state is more likely to induce a large loss of coercivity. In addition to the local stress states and strain levels themselves, the shape of the interfaces and the intergranular phases also makes a difference in determining the coercivity. Smoothing the edge and reducing the sharp angle of the triple regions in Nd-Fe-B magnets would be favorable for a coercivity enhancement.Comment: 9 figure

Effects of longevity and dependency rates on saving and growth: Evidence from a panel of cross countries

While earlier empirical studies found a negative saving effect of old-age dependency rates without considering longevity, recent studies have found that longevity has a positive effect on growth without considering old-age dependency rates. In this paper, we first justify the related yet independent roles of longevity and old-age dependency rates in determining saving and growth by using a growth model that encompasses both neoclassical and endogenous growth models as special cases. Using panel data from a recent World Bank data set, we then find that the longevity effect is positive and the dependency effect is negative in savings and investment regressions. The estimates indicate that the differences in the demographic variables across countries or over time can well explain the differences in aggregate savings rates. We also find that both population age structure and life expectancy are important contributing factors to growth.