DOI :10.26650/B/SS10.2021.013.28   IUP :10.26650/B/SS10.2021.013.28    Tam Metin (PDF)

Gelirin Sağlık Harcamaları Üzerindeki Asimetrik Etkisinin Panel Veri Modelleri ile Analizi

Ferda Yerdelen Tatoğlu

Gelirin sağlık harcamaları üzerindeki etkisi birçok analize konu olmuş ve yapılan çalışmaların çok büyük bir kısmında bu etkinin simetrik olduğu düşünülerek sonuçlar elde edilmeye çalışılmıştır. Ekonometride genel kullanım alanı olan simetrik regresyon model sonuçlarına göre, bir bağımsız değişkendeki bir birimlik artış ile azalışın bağımlı değişkende yarattığı etkinin yönü farklı olsa da şiddeti aynıdır. Oysa asimetrik teoriye göre, bir bağımsız değişkenin aynı miktardaki artış ve azalışı bağımlı değişkeni farklı oranlarda etkileyebilmektedir, bir başka ifade ile asimetrik davranış sergileyebilmektedir. Bu çalışmada, 2000-2018 döneminde 44 ülke için sağlık harcamalarının gelir esnekliğinin asimetrik davranış gösterip göstermediği incelenmiştir. Bu nedenle simetriklik varsayımı, artan gelirin sağlık harcamaları üzerindeki etkisinin düşen gelirin etkisinden farklı olup olmadığını araştırmak için esnetilmiştir. Sonuçlar, gelirdeki pozitif şokların sağlık harcamalarını negatif şoklardan fazla etkilediğini yani etkinin asimetrik olduğunu göstermektedir. Ayrıca sağlık harcamalarının gelir esnekliği birden küçük çıkmıştır, bu durum sağlık harcamalarının lüks değil gereklilik olduğu sonucuna ulaşılmasını sağlamaktadır.

DOI :10.26650/B/SS10.2021.013.28   IUP :10.26650/B/SS10.2021.013.28    Tam Metin (PDF)

Analysis of Asymmetric Effect on Health Expenditures of Income With Panel Data Models

Ferda Yerdelen Tatoğlu

In the literature, many analyses have been conducted on the effect of income on health expenditures. This effect is considered to be symmetrical in most of these studies. According to the results of the symmetric regression model, a one-unit increase or decrease in the independent variable has the same effect on the dependent variable. However, according to asymmetric theory, an equivalent increase or decrease of an independent variable can affect the dependent variable at different rates, or cause asymmetrical behavior in response. 

After 2010, studies were conducted using cross-sectional and time series data to estimate the asymmetric model. Asymmetry has been discussed by Chamlin and Cochran (1998), with the non-linear autoregressive moving average (ARIMA) model, and by Shin et al. (2014), with the non-linear autoregressive distributed lag (NARDL) model. Asymmetric studies with panel data are more recent. The panel NARDL model was first discussed by Salisu and Isah (2017). Conversely, studies about asymmetry in panel data regression models emerged after York and Light’s (2017) study. York and Light (2017) used the first difference model to estimate asymmetric panel data models and determined efficient estimators using robust standard errors. Allison (2019) proposed the generalized least squared (GLS) method to estimate this model and demonstrated that the GLS estimator produced unbiased and efficient estimators. According to this method, variables exhibiting asymmetric behavior are divided into positive and negative components, and, using these variables, the first difference regression model is estimated using ordinary least squares (OLS) with robust standard errors or GLS.

In this study, gross domestic product (GDP), life expectancy at birth (mean life expectancy) (LE) to represent technological progress, and the ratio of the population over 65 to the total population (AGE) were used as determinants of health expenditures (HE). Data for 44 countries between 2000 and 2018 were used. The data for all variables were obtained from the Organization of Economic Cooperation and Development (OECD) database. Firstly, the presence of individual effects and whether they were correlated with the independent variables was tested. After determining that there is an individual effect that is correlated with the independent variables, an F test was used to Both variables increase healthcare costs by increasing both the cost of care and the demand for medical treatments and research and development expenditures for the healthcare sector. A positive relationship between the aging population and public expenditures has been reported by Burner et al. (1992), Getzen (1992), Seshamani and Gray (2004), Yang et al. (2003), Lee and Miller (2002), Sanz and Velazquez (2007), and Sorensen (2013). determine whether  there the effect of income on HE was asymmetrical. If the effect of income on HE is found to be asymmetrical, this indicates that HE responds less to a decrease in income than to increase in income. Similar results in the literature have been reported by Parkin et al. (1987), Di-Matteo (2003), Freeman (2003), Dreger and Reimers (2005), Sen (2005), Costa-i Font et al. (2009), Baltagi and Moscone (2010), Moscone and Tosetti (2010), Ke et al. (2011), Farag et al. (2012), Acemoglu et al. (2013), Murthy and Okunade (2016), and Kouassi et al. (2018). A possible theoretical justification for the asymmetric effect of changes in income on HE may be demand irreversibility. According to this theory, consumers are less responsive to decreases than increases in income. When future prices and therefore expenditures are uncertain, price increases will cause individuals to increase healthcare expenditures (Maynard and Subramaniam, 2015). However, a similar effect is not observed in income decreases. Under this hypothesis, health demand will be more elastic given an increase in income. In addition, the inability of the government to make rapid policy changes, especially during economic crises, may be another reason for the asymmetric effect of income on HE. Since the income elasticity of HE is less than one, health services are considered a necessity and not a luxury. In addition, the effects of the population over 65 years of age and life expectancy at birth were found to be positive. Over the last 30 years, a decrease in the fertility rate has led to an increase in the life expectancy of the aging population, changes, and innovations in health services, and an improvement in living conditions, especially those of elderly individuals (such as Zweifel and Ferrari (1992), and Iliman and Tekeli (2017)). Both variables increase healthcare costs by increasing both the cost of care and the demand for medical treatments and research and development expenditures for the healthcare sector. A positive relationship between the aging population and public expenditures has been reported by Burner et al. (1992), Getzen (1992), Seshamani and Gray (2004), Yang et al. (2003), Lee and Miller (2002), Sanz and Velazquez (2007), and Sorensen (2013). 

The findings of this study indicate that healthcare spending is a necessity rather than a luxury. Therefore, policies should be implemented to increase healthcare expenditures in the countries in which healthcare expenditures are less than the OECD average. In recent years, the life expectancy at birth worldwide and the elderly population have increased. More attention should be paid to issues such as the development of innovative healthcare policies for the elderly, such as home care, healthcare, and public services.


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