Interdisciplinary Public Finance, Business and Economics Studies Volume III

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List of Contributors

Rıza Aşıkoğlu

Ph.D., Prof., Afyon Kocatepe University, Faculty of Economics and Administrative Sciences, Department of International Trade and Finance, riza@aku.edu.tr, ORCID: 0000-0003-4282-4561

Işıl Ayas

Ph.D., Assist. Prof., Sakarya University, Faculty of Political Sciences, Department of Public Finance, iyeter@sakarya.edu.tr, ORCID: 0000-0002-5441-006X

Münevver Bayar

Ph.D., Manager, Social Security Institution, munevverbayar@hotmail.com, ORCID: 0000-0002-8077-2160

Selahattin Bozkurt

Ph.D., Assist. Prof. Dr., Kütahya Dumlupınar University, History of the Republic of Turkey, selahattin.bozkurt@dpu.edu.tr, ORCID: 0000-0001-7676-7206

Şerif Canbay

Ph.D., Assist. Prof., Duzce University, Faculty of Political Sciences, Department of Economic, canbay.serif@gmail.com, ORCID: 0000-0001-6141-7510

İsmail Ciğerci

Ph.D., Assist. Prof., Afyon Kocatepe University, Faculty of Economics and Administrative Sciences, Department of Public Finance, icigerci@aku.edu.tr, ORCID: : 0000-0002-8858-5685

Mehmet Cıranoğlu

Ph.D., Research Assistant, Bursa Uludag University, Inegol Faculty of Business, Department of Business Administration, ciranoglu@uludag.edu.tr, ORCID: 0000-0002-7798-7099

Ramazan Durgut

Ph.D. iur., Assist. Prof., Istanbul University, Business School, Commercial Law Department, rdurgut@istanbul.edu.tr, ORCID: 0000-0002-9037-2005

Selami Erdoğan

Ph.D., Assist.Prof., Kutahya Dumlupınar University, Faculty of Administrative and Economics Sciences, Department of Public Administration, Kutahya-Turkey, selami.erdogan@dpu.edu.tr, ORCID: 0000-0002-2245-4105

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İbrahim Ethem Güney

Ph.D., Doha Representative, Central Bank of the Republic of Turkey, ethem. guney@tcmb.gov.tr, ORCID: 0000-0001-6890-205X

Eray Gemici

Ph.D., Assist. Prof., Gaziantep University, Islahiye Faculty of Economics and Administrative Sciences, Department of Business Administration, gemici@ gantep.edu.tr, ORCID: 0000-0001-5449-0568

Serkan Göksu

Ph.D., Lecturer. Afyon Kocatepe University, Vocational School of Dazkırı. sgoksu@aku.edu.tr, ORCID: 0000-0003-3261-6769

Ebru Gül Yılmaz

Ph.D., Assist. Prof., İstanbul Gelişim University, egyilmaz@gelisim.edu.tr, ORCID: 0000-0002-3610-4982

İskender Gümüş

Ph.D., Assist. Prof., Kirklareli University, Faculty of Economics and Administrative Sciences, Department of Labor Economics and Industrial Relations, iskender. gumus@klu.edu.tr, ORCID: 0000-0002-1428-0512

Erkam Hasim Bulut

Research Assistant, Istanbul University, Business School, Commercial Law Department,erkam.bulut@istanbul.edu.tr, ORCID: 0000-0001-8579-509X

Fikret Karakoç

Ph.D. Student, Kutahya Dumlupinar University fikret.karakoc@ogr.dpu.edu.tr, ORCID: 0000-0001-7974-3103

Yusuf Kaya

Ph.D., Assist.Prof., Pamukkale University, Department of Banking and Insurance, ykaya@pau.edu.tr, ORCID: 0000-0002-2076-9808

Ali Kestane

Ph.D., Kilis 7 Aralık Üniversitesi,, Faculty of Economics and Administrative Sciences, Department of Management, alikestane@kilis.edu.tr, ORCID: 0000-0002-7049-0354

Beyhan Kılınçer

Ph.D., Lecturer, Adiyaman University, Vocational School of Social Sciences, Department of Accounting and Tax, bkilincer@adiyaman.edu.tr, ORCID: 0000-0002-5638-8177

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Burcu Kıran Baygın

Ph.D., Prof., Istanbul University, Faculty of Economics, Department of Econometrics, 34452, Beyazit, Istanbul, Turkey. Tel: (212) 440-00-00 /11211. E-mail: kburcu@istanbul.edu.tr, ORCID: 0000-0002-4258-0870

İlhan Korkmaz

Ph.D., Assist. Prof., Kütahya Dumlupinar University, Faculty of Economics and Administrative Sciences, Department of Economics, ilhan.korkmaz@dpu.edu.tr, ORCID: 0000-0002-7503-6505

Niyazi Kurnaz

Ph.D. Prof., Kütahya Dumlupınar University,, Faculty of Economics and Administrative Sciences, Department of Management, niyazi.kurnaz@dpu.edu.tr, ORCID: 0000-0001-7019-0119

Wilkista Lore Obiero

Eskisehir Osmangazi University, Institute of Social Sciences, Department of Economics, lwilkista@gmail.com, ORCID: 0000-0002-0498-3142

Mediha Mine Çelikkol

Ph.D., Assist. Prof., Kütahya Dumlupinar University, Kütahya Vocational School of Social Sciences, Department of Banking and Insurance, mine.celikkol@dpu. edu.tr, ORCID: 0000-0001-7876-9483

Fulya Mısırdalı Yangil

Ph.D., Assoc. Prof., Dumlupınar University, Altıntaş Vocational School, Management&Organization, fulya.myangil@dpu.edu.tr, ORCID: 0000-00025746-3458

Serdar Ögel

Ph.D., Assist. Prof., Afyon Kocatepe Üniversity, Faculty of Economics and Administrative Sciences, Department of Business Administration, serdarogel@ aku.edu.tr, ORCID: 0000-0002-7151-1671

Yüksel Okşak

Ph.D., Assist. Prof., Bursa Uludağ University, İnegöl Faculty of Business, yukseloksak@uludag.edu.tr, ORCID: 0000-0001-8794-4597

Özer Özçelik

Ph.D., Assist. Prof., Kütahya Dumlupınar Üniversitesi, Faculty of Economics and Administrative Sciences, Department of Economics, ozer.ozcelik@dpu.edu.tr, ORCID: : 0000-0001-9164-5020

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Eda Özen

Ph.D., Assist. Prof., Bilecik Seyh Edebali University, Faculty of Economics and Administrative Sciences, Department of Economics, eda.ozen@bilecik.edu.tr, ORCID: 0000-0002-0818-1040

Derya Öztürk

Ph.D., Assoc.Prof., Ordu University, Unye Faculty of Economics and Administrative Sciences, Department of Business, deryaozturk@odu.edu.tr, ORCID: 0000-0001-5287-6600

Tufan Sarıtaş

Ph.D., Assist. Prof., Karamanoğlu Mehmetbey University, Faculty of Economics and Administrative Sciences, Department of Economics, tufansaritas@kmu.edu.tr, ORCID: 0000-0003-1728-2377

Yavuz Selim Düger

Ph.D., Assist. Prof., Kütahya Dumlupinar University, Faculty of Economics and Administrative Sciences, Department of International Trade and Finance, yselim.duger@dpu.edu.tr, ORCID: 0000-0003-3523-9671

Yavuz Selim Hacıhasanoğlu

Ph.D., Economist, Central Bank of the Republic of Turkey, yavuz.selim@tcmb. gov.tr. The views in this chapter are only those of the author and should not be interpreted as reflecting those of the Central Bank of the Republic of Turkey.

Mehmet Şengür

Ph.D., Assist. Prof., Eskisehir Osmangazi University, Faculty of Economics and Administrative Sciences, Department of Economics, msengur@ogu.edu.tr, ORCID: 0000-0002-2173-9977

Safiye Süreyya Bengül

Ph.D., Assist. Prof., Kütahya Dumlupinar University, Kütahya Vocational School of Social Sciences, Department of Marketing, ssureyya.bengul@dpu.edu.tr, ORCID: 0000-0003-0773-0690

Figen Taşkın

Ph.D, Assist. Prof., Ordu University, Unye Faculty of Economics and Administrative Sciences, Department of Political Science and Public Administration, figentaskin@odu.edu.tr, ORCID: 0000-0001-9752-3139

Selim Tüzüntürk

Ph.D., Assoc. Prof., Bursa Uludağ University, Department of Econometrics, selimtuzunturk@uludag.edu.tr, ORCID: 0000-0002-8987-2280

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Mehmet Utku

Ph.D., Assist.Prof., Pamukkale University, Department of Business Administration, mutku@pau.edu.tr, ORCID: 0000-0002-7076-6891

Nuran Varışlı

Ph.D., Expert, Republic of Turkey Social Security Institution, gulmennuran@hotmail.com, ORCID: 0000-0002-0657-756X

Setenay Yağmur

Ph.D., setenayyagmur@gmail.com, ORCID:0000-0001-5765-5962

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Burcu Kıran Baygın

Convergence of Per Capita Health Expenditures: Evidence from Selected OECD Countries

1 Introduction

The concept of human capital is first introduced by Schultz (1961) and means increasing the number of people with skills, education and experience. It is very critical for a country’s economic and political development. Therefore, human capital development refers to the investment in human and also creative and productive development of investment. Human capital investments increase both human and physical capital investments by creating an overflow-spreading effect, thus affecting economic growth positively (Barro, 1991). Factors which play a critical role in the increase of human capital stock are considered as components of human capital, and these components are divided into five categories: (i) health services which affect individuals’ life expectancy, life force, and energy (ii) educations organized by companies (iii) formal education at primary, secondary and higher education level (iv) working programs which are not organized by companies for adults, especially including agricultural progress programs (v) individual or family migrations to adapt to changing job opportunities. In fact, education and health are the most important of these categorized components. Because healthy, educated and skilled labor force constitute comprehensive and productive capital (Schultz, 1961).

The basic condition for individuals to get education and engage in economic activities is to be healthy. The government plays an active role in this field due to the realization of the growth target of health expenditures. On the other hand, health is semi-public goods. The most important health indicators used in country comparisons are birth rate, mortality rate, infant mortality rate, total fertility rate, life expectancy at birth, share of health expenditures in gross domestic product (GDP) and per capita health expenditures. In recent years, convergence in the healthcare system has become an important research topic with the rapid increase in health expenditures and the increasingly similar health policies.

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The term of convergence can be identified as “the result of a process in which the structures of different industrial societies come increasingly to resemble each other” (Jary and Jary, 1991). Economic convergence is based on neo-classical growth theory and has a simple notion. According to neo-classical growth models, if the countries only differ from each other in the initial level of per capita income and capital, they will reach the same steady – state level, since the productivity of capital in the poor countries is higher than that of the rich countries. This means that the poor countries will experience a higher growth rate than rich countries. Consequently, the former will eventually catch-up, the disparity gap will shrink and eventually close over time. On the other side, if the growth rates of the rich countries are higher than the rates of poor countries, the disparity gap will increase over time. In this case, it is said that these countries are diverging from each other (Fallahi, 2011). Over time, the idea of convergence is used to assess the transformations of other areas of economic life. An example of this is the use of convergence in the analysis of health expenditure.

Borrowing convergence concept from neo-classical growth theory, some studies have recently considered health expenditure convergence between countries and reached mixed results (Hitiris, 1997; McCoskey and Selden, 1998; Nixon, 1999; Hitiris and Nixon, 2001; Jewell et al., 2003; Carrion-i-Silvestre, 2005; Narayan, 2007; Aslan, 2008; Kerem et al., 2008; Wang, 2008; Alcalde-Unzu et al. 2009; Fallahi, 2011; Schmitt and Starke, 2011; Panopoulou and Pantelidis, 2012).

This paper examines the convergence of per capita health expenditures for selected 21 Organisation for Economic Co-operation and Development (OECD) countries over the period from 1975 through 2018 by using Papell and Prodan (2006) unit root test with one and two endogenous structural breaks. According to the OECD Health Statistics report published in 2019, health expenditure as a share of GDP was 8.8 %, on average across the OECD countries, in 2017. The share of GDP is expected to stay at 8.8 % in 2018. Health expenditure in 2017 was highest in the United States (17.1 %). The second and third highest spenders were Switzerland (12.3 %) and France (11.3 %), respectively. On the other hand, the lowest spenders in terms of share of GDP were Turkey (4.2 %), Luxembourg (5.4 %) and Mexico (5.4 %). Based on the per capita terms, health expenditure in 2017 is USD 3 854 on average. The averaged health expenditure per capita for the United States was USD 10 206, more than double the OECD average. There are strong reasons for the high levels of per capita health expenditures in the United States. One of them is that the USA has a much higher capacity in high-technology facilities compared to other countries. Second one is that the USA tends to adopt new medical technologies more rapidly than other countries (Anderson et al., 2000, 154). The next highest level of per capita health expenditures, above the OECD average, occurred in Switzerland (USD 7 147) and Norway (USD 6 064) (OECD, 2019).

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The remainder of the paper is organized as follows: Section 2 lays out the basics of the Papell and Prodan(2006) unit root test with one and two endogenous structural breaks, while Section 3 describes the data and reports the results. Finally, Section 4 concludes the paper.

2 Papell and Prodan (2006) Unit Root Test with One and Two Endogenous Structural Breaks

Papell and Prodan (2006) suggested unit root tests with one and two structural breaks that both account for structural change and maintain a long-run mean or trend by considering an Additive Outlier (AO) type model to model changes that occur instantaneously. The Additive Outlier model is estimated in two step. As a first step, the deterministic part of the analyzed series (y_t) is removed by using following regression equation for a value of the break point TB, with 0.10T < TB < 0.90T (where T is the sample size):

Here, the dummy variable DU_t is constructed as follows:

The reason of using 0.10T < TB < 0.90T trimming is to avoid finding spurious breaks at the beginning and end of the sample. As a second step, the unit root test is applied by calculating the t statistic for TB in the following regression:

where

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To ensure that t statistic on α is invariant to the value of truncation lag parameter k, it is needed to include k + 1 dummy variables. The recursive procedure of choosing k starts with k_max = 8 and it is repeated until the last lag is significant by using critical value of 1.645. The break date TB is choosen by minimizing the t-statistic on α. Statistics are calculated for all break dates based on the trimming.

As a different specification, Papell and Prodan (2006) include a time trend to the previous Additive Outlier model and perform unit root tests by permitting shifts in the intercept at an unknown time. They again use two step procedure. As a first step, to remove the deterministic part of the considered y_t series, the following regression is estimated:

Here, 10 % trimming is used to avoid spurious breaks. As a second step, the previous equation

is re-estimated. The unit root test is applied by using the t statistic for α = 0.

By including two endogenous structural breaks, Papell and Prodan (2006) extend the Additive Outlier model. The deterministic part of the y_t series is removed by including two break points TB₁ and TB₂ with 0.10T < TB_i < 0.90T (where T is the sample size and i = 1, 2) as follows:

where

As a second step of the process with two structural breaks, following regression equation is estimated:

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Here,

Finally, Papell and Prodan (2006) remove the deterministic part of the y_t series by using regression equation with two structural breaks in below: