Producer Support Estimates (PSEs) for agriculture in developing countries

In many developing countries, governments rely on price-based measures (including border protection and subsidies on inputs and outputs) more than on budgetary payments to achieve agricultural policy objectives defined to include price stabilization or food self-sufficiency. Assessing the effects of these price-based measures is thus important to evaluating whether agriculture is being protected or disprotected by commodity or in the aggregate. This aspect of producer support estimates (PSEs) is simple to describe conceptually but difficult to evaluate well empirically. Developing countries may face higher international transport and port costs for imports and exports than developed countries or may have substantial internal handling, transportation and processing costs. Separating these structural effects on farmers from agricultural policy effects that drive a wedge between the domestic farmgate price and an adjusted international reference price requires extensive data and judgments. In this paper, we describe the PSE measurement issues and illustrate their importance. We estimate product-specific market price support, budget expenditures and PSEs for three important agricultural commodities (wheat, rice and corn) in India (1985-2002), using representative disaggregated state-level results, and for five commodities (wheat, rice, corn, soybeans and sugar) in China (1995-2001). The results for India suggest that ignoring factors such as internal transport costs, marketing margins and quality differences can result in inaccurate price support estimates and PSEs that may be of the wrong sign. We also explore how relaxing or changing certain standard PSE assumptions (such as altering the “scaling up” procedure or computing the PSE as a percentage of value of production at world reference prices) can have large impacts on the results. Finally, for commodities that are near self-sufficiency, we follow Byerlee and Morris (1993) and define a relevant adjusted reference price based on the relationship between an estimated autarky price and the import and export prices. We discuss this procedure and use the resulting reference prices to compute the market price support component of the PSE for India. Based on our three-commodity PSEs for India, support is largely counter-cyclical, rising when world prices are low (as in the late 1980s and 1990s) and falling when world prices strengthen (as in the mid 1990s). From our more preliminary five-commodity PSE estimates for China, a trend decline in disprotection is more evident. Further research is needed to confirm and elaborate on these results.

AGRICULTURAL POLICY INTERVENTIONS IN DEVELOPING COUNTRIES: MAPPING THE NATURE, DEGREE AND PROGRESS OF REFORMS

Replaced with revised version of paper 07/16/04.International Development,

Non-ergodic Convergence Analysis of Heavy-Ball Algorithms

In this paper, we revisit the convergence of the Heavy-ball method, and present improved convergence complexity results in the convex setting. We provide the first non-ergodic O(1/k) rate result of the Heavy-ball algorithm with constant step size for coercive objective functions. For objective functions satisfying a relaxed strongly convex condition, the linear convergence is established under weaker assumptions on the step size and inertial parameter than made in the existing literature. We extend our results to multi-block version of the algorithm with both the cyclic and stochastic update rules. In addition, our results can also be extended to decentralized optimization, where the ergodic analysis is not applicable

Study of Bc−B_{c}^{-} →{\to} J/ψπ−J/{\psi}{\pi}^{-}, ηcπ−{\eta}_{c}{\pi}^{-} Decays with QCD Factorization

The $B_{c}$ ${\to}$ $J/{\psi}{\pi}$, ${\eta}_{c}{\pi}$ decays are studied in the scheme of the QCD factorization approach. The branching ratios are calculated with the asymptotic distribution amplitude of the pion. The charm quark mass effect is considered. We find that the mass effect on the branching ratios is small.Comment: 20 pages, 3 figures, 3 table

SASG: Sparsification with Adaptive Stochastic Gradients for Communication-efficient Distributed Learning

Stochastic optimization algorithms implemented on distributed computing architectures are increasingly used to tackle large-scale machine learning applications. A key bottleneck in such distributed systems is the communication overhead for exchanging information such as stochastic gradients between different workers. Sparse communication with memory and the adaptive aggregation methodology are two successful frameworks among the various techniques proposed to address this issue. In this paper, we creatively exploit the advantages of Sparse communication and Adaptive aggregated Stochastic Gradients to design a communication-efficient distributed algorithm named SASG. Specifically, we first determine the workers that need to communicate based on the adaptive aggregation rule and then sparse this transmitted information. Therefore, our algorithm reduces both the overhead of communication rounds and the number of communication bits in the distributed system. We define an auxiliary sequence and give convergence results of the algorithm with the help of Lyapunov function analysis. Experiments on training deep neural networks show that our algorithm can significantly reduce the number of communication rounds and bits compared to the previous methods, with little or no impact on training and testing accuracy.Comment: 12 pages, 5 figure