Does Internal Migration Lead to Faster Regional Convergence in Turkey? An Empirical Investigation

In this study, we examine whether internal migration in the last 30 years in Turkey has had any effect on the speed of convergence across Turkish provinces. According to our results, contrary to the predictions of the standard neoclassical theory, for 1975-2000,internal migration is not conducive to faster convergence across provinces in Turkey. One probable reason is that marginal returns to capital in most net outmigration provinces and regions are relatively lower than those in the net in-migration provinces and regions in Turkey. Accordingly, the incentives to invest in capital in net-out migration regions may well be less than those in the net in-migration regions.Faced with lower investment in gross capital formation, and thus lower economic growth, net out-migration provinces and regions may not benefit from out-migration in terms of convergence in per capita income.

Regional convergence and the causal impact of migration on regional growth rates

The standard growth theory predicts that allowing for labor mobility across regions would increase the speed of convergence in per capita income levels and that migration has a negative causal impact on regional growth rates. Although the empirical literature has uncovered some evidence for the former implication, the latter has not been verified empirically. This paper provides empirical evidence for the negative causal impact of migration on provincial growth rates in a developing country with a high level of internal migration that is characterized by unskilled labor exiting rural areas for urban centers. We utilize instrumental variables estimation method with an instrument unique to the country examined and also control for provincial fixed effects.Regional convergence; Regional growth; Internal migration; Fixed effects; IV estimation

International Capital Mobility and Factor Reallocation in a Multisector Economy

This paper examines the effects of international capital flows in a small open econ omy utilizing a dynamic general equilibrium framework based on a three-sector Ramsey growth model. In order to analyze the impact of international capital mobility on production, consumption and allocation of resources across three sectors ,two different economic environments are modelled. The first model represents an open economy with capital mobility (a more comprehensive environment),and the second model introduces a closed economy with no capital mobility. Numerical applications of the models use data from the Turkish economy for the year 2002. The numerical results demonstrate that the presence of capital mobility, despite being limited by a borrowing constraint, reverses the impact of economic growth on production and resource allocation. The results also show that while production in the closed economy model simply adjusts to domestic demand, that of the open economy model is not constrained by it. Results further point that although there is positive growth in income and output in both environments, income growth in the capital mobility environment falls short of that in the no capital mobility environment. This result can be attributed to the relatively slower accumulation of capi tal in the former, which may be compensated by a positive rate of technological progress to accompany international capital flows.International Capital Flows,Human Capital, Multisector economy,Borrowing Constraint

Exactly solvable variable parametric Burgers type models

Exactly solvable variable parametric Burgers type equations in one-dimension are introduced, and two different approaches for solving the corresponding initial value problems are given. The first one is using the relationship between the variable parametric models and their standard counterparts. The second approach is a direct linearization of the variable parametric Burgers model to a variable parametric parabolic model via a generalized Cole-Hopf transform. Eventually, the problem of finding analytic and exact solutions of the variable parametric models reduces to that of solving a corresponding second order linear ODE with time dependent coefficients. This makes our results applicable to a wide class of exactly solvable Burgers type equations related with the classical Sturm-Liouville problems for the orthogonal polynomials

Controlled Sensing for Multihypothesis Testing

The problem of multiple hypothesis testing with observation control is considered in both fixed sample size and sequential settings. In the fixed sample size setting, for binary hypothesis testing, the optimal exponent for the maximal error probability corresponds to the maximum Chernoff information over the choice of controls, and a pure stationary open-loop control policy is asymptotically optimal within the larger class of all causal control policies. For multihypothesis testing in the fixed sample size setting, lower and upper bounds on the optimal error exponent are derived. It is also shown through an example with three hypotheses that the optimal causal control policy can be strictly better than the optimal open-loop control policy. In the sequential setting, a test based on earlier work by Chernoff for binary hypothesis testing, is shown to be first-order asymptotically optimal for multihypothesis testing in a strong sense, using the notion of decision making risk in place of the overall probability of error. Another test is also designed to meet hard risk constrains while retaining asymptotic optimality. The role of past information and randomization in designing optimal control policies is discussed.Comment: To appear in the Transactions on Automatic Contro