Academic journal article Journal of Economics, Finance and Administrative Science

Is the Health Care Price Inflation in US Urban Areas Stationary? Evidence from Panel Unit Root Tests

Academic journal article Journal of Economics, Finance and Administrative Science

Is the Health Care Price Inflation in US Urban Areas Stationary? Evidence from Panel Unit Root Tests

Article excerpt

1. Introduction

Applied economists are increasingly interested in studying the relationship between inflation and other economic variables (Thanh, 2015; Nguyen, 2015). This requires stationarity of the time-series data of the variables, in levels or when differenced, to avoid spurious regression parameter estimates. More specifically, for decades, economists have been testing whether the inflation rate series are stationary at the regional or national level in developed countries and in varying panels of the Organization for Economic Cooperation and Development (OECD) countries (Rose, 1988; Johansen, 1992; Culver and Papell, 1997; Ericsson et al, 1998; Crowder and Wohar, 1999; Lee and, 2001; Rapach, 2002; Holmes, 2002; Charmeza et al., 2005; Basher and Westerlund, 2006; Lee and Chang, 2007; Romero-Avila and Usabiaga, 2009a, 2009b). However, empirical evidence on the stochastic properties of the inflation rate series is mixed. For example, while Lee and Chang (2007) and Culver and Papell (1997) claim that inflation rates in the OECD countries are stationary, integrated of the order of zero, I (0), Rodrizuez (2004) and Arize (2005) report that inflation rates in the Latin American and many developing countries are non-stationary, respectively, and therefore, they are integrated of the order one, I (1).

Whether the inflation rate is stationary or not has policy implications. If, for instance, the inflationary rate series is non-stationary and therefore has a unit root, then statistical inference in econometric modeling using such a variable will be spurious. Also, monetary policy actions in the presence of non-stationary inflation rate will result in permanent shocks to the system and therefore the inflation rate will not be mean reverting. Moreover, findings on stochastic properties of the inflation rate have theoretical implications for the validity of the Phillips curve phenomenon, the relevance of the Keynesian theory, and inter-temporal allocation decisions concerning saving and investment. The presence of a unit root in the inflation rate series and the attendant problem of persistence are of significance for policy effectiveness, inflation rate forecasting and the underlying theoretical models--see Levin and Piger (2004), O'Reilly and Whelan (2004) and Corvoisier and Mojon (2005). Therefore, fiscal and monetary policy authorities should be aware of the degree of persistence of inflation rate and, therefore, the differences in speed of its adjustment when designing effective inflationary containment policies. For example, if the aggregate inflation rate is non-stationary, I ~ (1), and hence highly persistent, monetary policy actions aimed at containing the inflation rate will be futile and result in a permanent effect.

Consequently, economists, economic analysts and policy decision makers currently seek an understanding and evaluation of the time-series properties of inflation rates based on data at various aggregation levels. This is particularly important in the case of health-care price inflation rate (hereafter, health-care inflation rate) in urban areas. More specifically, the emerging evidence from health-care markets from implementing the 2010 US Affordable Care Act (ACA) reveals wide variances in the health-care coverage insurance rates, costs and prices across the major urban areas, even for preventive primary care visits[1]. More recently (Joszt, 2015), the Healthcare Cost Institute (HCI) created the Healthy Marketplace Index, a series of metrics measuring the economic performance (e.g. pricing) in health-care markets across the USA. The HCI's price index larger (smaller) than 1.0 indicates health-care markets with higher (less) than average prices[2]. This suggests that when designing health-care policies, it is critical to provide the insurers and policy makers with reliable guidance as to whether health-care price increases are stationary, using panel unit root tests that have more statistical power and relatively less size distortions. …

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