THE EFFECTIVENESS OF HEALTH BUDGET IN REDUCING POVERTY: EVIDENCE IN INDONESIA

IDARYANI

M.Si, Economics and Business Faculty of Universitas Syiah Kuala, Indonesia

idaryaniaceh1@gmail.com

Masbar RAJA

Prof, Economics and Business Faculty of Universitas Syiah Kuala, Indonesia

raja.masbar@unsyiah.ac.id

ALIASUDDIN

Dr, Economics and Business Faculty of Universitas Syiah Kuala, Indonesia

aliasuddin@unsyiah.ac.id

Nasir MUHAMMAD

Dr, Economics and Business Faculty of Universitas Syiah Kuala, Indonesia

nasirmsi@unsyiah.ac.id

Abstract

The purpose of this study is to analyze the effectiveness of health expenditures in reducing poverty in Indonesia. The data used was panel data from three specific autonomous regions: Aceh, Papua, and West Papua, data from 2006-2017. The method of analysis used in the study was the ARDL Panel model. The results of the study show that in the short term, health expenditures o not affect poverty in the autonomous regions. The results from each region showed no short-term effect. Long-term estimates show that health spending can reduce poverty by up to 6 percent assuming cateris paribus. Adjustments of these impacts will occur every 9.6 months. This study recommends that the government increases the health budget so that the poor can get protection and avoid health problems. The study also recommends increased regulation of health expenditures to make it more effective and have an impact in the short term.

Keywords: Health Budget, Poverty, ARDL Panel, Special Autonomy

JEL classification: C23, H51, I38
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SPATIAL ANALYSIS OF THE IMPACT OF MIGRATION ON REGIONAL GROWTH IN IRAN (2006-16)

Shekoofeh FARAHMAND

Associate Professor, Economics Department, University of Isfahan, Iran

sh.farahmand@ase.ui.ac.ir

Narges GHASEMIAN

Ph.D candidate of economics, Alzahra University of Tehran, Iran

N.Ghasemian@alzahra.ac.ir

Abstract

One of the most important applications of economic growth models is for regional economic growth. In regional growth studies, it is necessary to consider spatial effects because of spatial dependence among the growth rates of regions. This research investigates the impact between net migration and its spatial lag on regional growth, based on the neoclassical (Solow) growth model. The used model in the study is the Dynamic Panel Data (DPD) which has been specified as a Spatial Durbin Model (SDM) and estimated by the spatial generalized method of moments (SGMM). The specified model has been tested for the 30 provinces of Iran in the period of 2006-16. The estimated results show that the time-lagged dependent variable had a positive and highly significant effect on income per capita. The impact of initial income per capita on growth is negative, and the convergence hypothesis is thus accepted. That is, poor provinces grow faster than the rich. The income per capita and growth are positively related to net migration rate. Expectedly, the new coming people to a province would increase income per capita and growth. The estimated coefficient of the spatial lag of the dependent variable is statistically significant and demonstrates spatial dependence in income as well as economic growth among the provinces of Iran. Every province’s growth rate was positively impacted by the economic growth of its neighbors. However, net migration has no spatial effect on income per capita and growth. In other words, the regional economic growth has not been influenced by migration to neighboring provinces.

Keywords: Neoclassical growth model, convergence, migration, spatial Durbin model, spatial generalized method of moments.

JEL classification: O47, C23, R23
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BDI’s CORRELATION WITH LEADING ECONOMIC INDICATORS

Theodore PELAGIDIS

Professor, University of Piraeus & NR Senior Fellow, Brookings Institution, US. 21, Lambraki Ave.,GR-18533

pelagidi@unipi.gr

Evgenia TSAHALI

University of Piraeus,

evgtsahali@yahoo.gr

Abstract

The aim of this paper is to investigate the correlation between the Baltic Dry Index (BDI) and certain leading economic indicators. We follow a different path than the existing literature follows. In particular, using a multi-linear regression method and defining the BDI index as a dependent variable, we seek to determine the multiple relations of the independent variables regarding the BDI value. We are looking at whether the BDI is a representative indicator not only for the shipping industry itself, but also for the whole economic and financial environment in which the shipping industry operates.

Keywords: Transportation Economics, General Financial Markets, Financial Securities

JEL classification: R4, R42, G1