Growth and Election Outcomes in a Developing Country.

With the exception Brander and Drazen (2008), who use a comprehensive cross-country database consisting of both developed and developing countries, the hypothesis that rapid growth helps incumbents win elections has been tested exclusively for the developed countries (e.g., Ray Fair 1978). But since sustained rapid growth offers the prospect of pulling vast numbers of the voters out of poverty within a generation, such an effect is far more likely to be present in the developing rather than developed countries. In this paper, we offer the first test of the hypothesis on a large developing and poor country, India, which has seen its economy grow 8 to 9 percent recently. We first generalize the Fair model to allow for multiple candidates instead for just two and then test it using crossstate data. We find quantitatively large and statistically robust effect of growth on the prospects of the candidates of the state incumbent parties to win elections. Specifically, we use the data on 422 candidates in the 2009 parliamentary elections and show that the candidates of incumbent parties in high-growth states have much better prospects of victory than those in low-growth states.

Free Trade Areas and Rules of Origin: Economics and Politics

We incorporate intermediate inputs into a small-union general- equilibrium model and develop the welfare economics of preferential trading under the rules of origin. Combining this analysis with the Grossman-Helpman political-economy model, we demonstrate that the rules of origin can improve the political viability of FTAs. Two interesting outcomes are derived. First, an FTA that lowered joint welfare of the union and was voted down in the absence of the rules of origin may become feasible in the presence of these rules. Second, an FTA that increased joint welfare of the union but was voted down in the absence of the rules of origin may become acceptable in the presence of these rules but it may also turn welfare inferior to status quo.

Did the Multi-fiber Agreement Make the NAFTA Politically More Acceptable? A Theoretical Analysis.

The central question addressed in this paper is whether the presence of the MFA made the NAFTA politically more acceptable. Assuming that the government maximizes a weighted sum of welfare and producer profits, we derive four key results. First, taking the initial level of trade restriction as exogenously given, it is possible for an FTA to be endorsed by both parties under the MFA-like quota in one country though it is unambiguously rejected under a tariff that provides equal protection. Second, if the initial MFA quota is itself chosen endogenously, as long as all quota rents accrue to exporting countries, the quota is set so as to yield either autarky or free trade. Third, an intermediate outcome can obtain if quota rents are shared between the trading partners as is true, for example, under a tariff quota. Depending on the degree of the government’s bias in favor of producers, this outcome may be more or less restrictive than that obtained under a tariff. Finally, assuming parameter values that give rise to the intermediate outcome initially, it remains possible for an FTA to be endorsed under the MFA-type quota when it is turned down by one of the potential partners under a tariff. But it is now also possible for the opposite to happen: an FTA that is endorsed under a tariff may be turned down under the MFA-type quota.

India: Election Outcomes and Economic Performance

In this paper we provide the first analysis of the relationship of growth to election outcomes in India. Using a comprehensive data set consisting of all candidates contesting the election, we also provide the first systematic quantitative analysis of the 2009 Lok Sabha elections. Our key result is that superior growth performance at the level of the state gives a definite advantage to the candidates of the state incumbent party in the constituencies of that state. Conversely, poor growth performance of a state is associated with poor electoral performance by the candidates of the state incumbent party in the constituencies of that state. We offer two additional results: personal characteristics such as education and wealth have at most a small impact on election outcomes; and, at least in the 2009 election, incumbency at all levels contributed positively to election prospects of a candidate

Minimum Cost Homomorphisms to Reflexive Digraphs

For digraphs $G$ and $H$, a homomorphism of $G$ to $H$ is a mapping $f:\ V(G)\dom V(H)$such that$uv\in A(G)$implies$f(u)f(v)\in A(H)$. If moreover each vertex$u \in V(G)$is associated with costs$c_i(u), i \in V(H)$, then the cost of a homomorphism$f$is$\sum_{u\in V(G)}c_{f(u)}(u)$. For each fixed digraph$H, the {\em minimum cost homomorphism problem} for H$, denoted MinHOM($H$), is the following problem. Given an input digraph$G$, together with costs$c_i(u)$,$u\in V(G)$,$i\in V(H)$, and an integer$k$, decide if$G$admits a homomorphism to$H$of cost not exceeding$k. We focus on the minimum cost homomorphism problem for {\em reflexive} digraphs H$(every vertex of$H$has a loop). It is known that the problem MinHOM($H$) is polynomial time solvable if the digraph$H has a {\em Min-Max ordering}, i.e., if its vertices can be linearly ordered by <$so that$i<j, s<r$and$ir, js \in A(H)$imply that$is \in A(H)$and$jr \in A(H)$. We give a forbidden induced subgraph characterization of reflexive digraphs with a Min-Max ordering; our characterization implies a polynomial time test for the existence of a Min-Max ordering. Using this characterization, we show that for a reflexive digraph$H$ which does not admit a Min-Max ordering, the minimum cost homomorphism problem is NP-complete. Thus we obtain a full dichotomy classification of the complexity of minimum cost homomorphism problems for reflexive digraphs

A Deep Generative Framework for Paraphrase Generation

Paraphrase generation is an important problem in NLP, especially in question answering, information retrieval, information extraction, conversation systems, to name a few. In this paper, we address the problem of generating paraphrases automatically. Our proposed method is based on a combination of deep generative models (VAE) with sequence-to-sequence models (LSTM) to generate paraphrases, given an input sentence. Traditional VAEs when combined with recurrent neural networks can generate free text but they are not suitable for paraphrase generation for a given sentence. We address this problem by conditioning the both, encoder and decoder sides of VAE, on the original sentence, so that it can generate the given sentence's paraphrases. Unlike most existing models, our model is simple, modular and can generate multiple paraphrases, for a given sentence. Quantitative evaluation of the proposed method on a benchmark paraphrase dataset demonstrates its efficacy, and its performance improvement over the state-of-the-art methods by a significant margin, whereas qualitative human evaluation indicate that the generated paraphrases are well-formed, grammatically correct, and are relevant to the input sentence. Furthermore, we evaluate our method on a newly released question paraphrase dataset, and establish a new baseline for future research