Error Correction Coefficients Research Articles

Resiliency of healthcare expenditure to income shock: Evidence from dynamic heterogeneous panels.

Using the World Bank data over the period of 1960-2019, this study aims at estimating the resiliency of health expenditures against gross domestic product (GDP). Long-run and short-run elasticities are calculated using the type of panel time series methods that are exclusively designed for dynamic heterogeneous panels: Mean Group, Pooled Mean Group, and Dynamic Fixed Effects estimators. These methods permit better estimations of elasticity with considerable heterogeneity across the 177 countries included in this study. Along with a standard elasticity estimation, this study estimates country-specific long-run and short-run elasticities along with error correction components. The study finds that the long-run elasticity of income is very close to unity, but short-run coefficients are insignificant for most nations. In addition, most countries revert to long-run equilibrium reasonably quickly if there is shock as the error correction coefficients are negative and, in many cases, very close to one. While for most developed countries, the short-run elasticities are lower in comparison with the short-run elasticities of developing countries indicating that many developing countries may face a larger decrease in health expenditure with the forecasted decline in income due to impending economic recession. Therefore, although this study is not directly intended to capture the post-COVID-19 effects, the study estimates may project the potential responses in health expenditure across countries due to potential income shocks.

The Effect of Information Communication Technology (ICT) on Health Outcomes: Evidence from BRICS-T Countries

This study analyzes the effects information and communications technology (ICTs) have had on health outcomes on Brazil, Russia, India, China, South Africa (BRICS countries), and Turkey both on a panel and country basis using data from the period 1990 to 2018. The study has created three models. According to the general findings obtained for the panel, the error correction coefficients of the models other than Model II are negative and statistically significant. Based on the variables of income level, number of physicians, education level, and CO2 emissions used in Model I, the number of physicians and education level are seen to negatively affect life expectancy both in the short and long terms, contrary to theoretical expectations, while income level positively and CO2 emissions negatively affect life expectancy. The number of mobile users represents ICTs and negatively affects life expectancy both in the long and short term. Model III includes number of Internet subscribers, and all variables in this model except number of physicians support theoretical expectations. Accordingly, education and income levels have positive effects, and CO2 emissions have a negative effect. The number of Internet subscribers has both long- and short-term negative effects. When evaluating the findings according to country groups, the variable of income level positively and CO2 emissions negatively affect life expectancy in all countries. The variable of number of physicians has a negative value in all models and countries except for China in Model II. Similarly, the variable of education level generally has a negative impact in all models except Model III. All the ICT variables have negative values and negatively affect life expectancy.

Are the Indian Ragi Markets Integrated?

The Indian consumers and policymakers recognized finger millet (Ragi) increasingly as a nutritious staple. Karnataka, Uttrakhand, Maharashtra, and Tamil Nadu are the major ragi producing States contributing 90 percent of the Indian Ragi production. Various initiatives in recent years have aimed at promoting agricultural market integration. The present study aimed at testing the integration across the ragi markets in Tamil Nadu. The ADF test was used to assess the stationarity, Johansen cointegration, and the VECM model was used to analyze the long-term cointegration among the markets. Granger causality was used to assess the direction of the flow of information across markets. All the price series were first difference stationary. There existed two cointegration equations depicting the long-term integration across the markets. In the majority of the selected markets, a bidirectional flow of information was observed. Chinthamani and Tumkur markets error correction coefficients were significant, indicating that they will return to equilibrium in the short run by making corrections. Chinthamnai price influenced the Tumkur, Hosur, and Denkanikottai price at one month lag. The Tumkur price was influenced by its one-month lag and Hosur and Vellore one-month lag price. Tumkur and Vellore influence Hosur price by one month lag. The analysis found that Indian ragi markets were integrated in the long run.

Döviz Kuru, Faiz Oranı ve Enflasyon İle BİST Tüm ve BİST Sektörel Endeksler Arasındaki İlişkinin Ampirik Analizi

The purpose of this study is to determine the short and long-term relationships for the period of November 2009-December 2019, between exchange rate, interest rate and inflation, with five stock indices, which are traded in Istanbul Stock Exchange and have the highest trading volume. The analysis method used in the study is the ARDL bounds test. According to the obtained results; it is showed that the increase in the exchange rate decreased the stock indices in short and long run, these effects are only statistically significant in short run. It has been determined that the increase in interest rates in short and long run also caused a decrease in all examined indices. Relationship between interest rates and stock market indices is found to be statistically significant in the ISE All, ISE Financial and ISE Industrial indices in long run; and in the ISE Bank in short run. It has been determined that the increase in inflation in long run positively and in short run negatively affected all examined indexes. It is concluded that the long run relationship between inflation and ISE All, ISE Financial, ISE Services indices; and short run relationship of ISE All, ISE Financial, ISE Industrial indices are statistically significant. According to the short-term analysis results; it has been determined that error correction coefficients were negative and statistically significant in all models.

Time-varying information share and autoregressive loading factors: evidence from S&P 500 cash and E-mini futures markets

The error correction coefficients, known as the loading factors, are a key component for information share. To date, only constant loading factors have been considered for information share. This paper attempts to consider the autoregressive loading factors and their implications on the information share. Based on the minute-by-minute data from the S&P 500 cash and E-mini futures markets, this paper reveals that the loading factors are indeed autoregressive. Furthermore, we propose three AR(1) processes for the loading factors and assess their performance in information share compared to the constant loading factor model. Overall, this research provides supporting empirical evidence for using autoregressive loading factors for the information share measurement.

Estimation of Impedance and Susceptance Parameters of a 3-Phase Cable System Using PMU Data

This paper proposes a new regression-based method to estimate resistance, reactance, and susceptance parameters of a 3-phase cable segment using phasor measurement unit (PMU) data. The novelty of this method is that it gives accurate parameter estimates in the presence of unknown bias errors in the measurements. Bias errors are fixed errors present in the measurement equipment and have been neglected in previous such attempts of estimating parameters of a 3-phase line or cable segment. In power system networks, the sensors used for current and voltage measurements have inherent magnitude and phase errors whose measurements need to be corrected using calibrated correction coefficients. Neglecting or using wrong error correction coefficients causes fixed bias errors in the measured current and voltage signals. Measured current and voltage signals at different time instances are the variables in the regression model used to estimate the cable parameters. Thus, the bias errors in the sensors become fixed errors in the variables. This error in variables leads to inaccuracy in the estimated parameters. To avoid this, the proposed method uses a new regression model using extra parameters which facilitate the modeling of present but unknown bias errors in the measurement system. These added parameters account for the errors present in the non- or wrongly calibrated sensors. Apart from the measurement bias, random measurement errors also contribute to the total uncertainty of the estimated parameters. This paper also presents and compares methods to estimate the total uncertainty in the estimated parameters caused by the bias and random errors present in the measurement system. Results from simulation-based and laboratory experiments are presented to show the efficacy of the proposed method. A discussion about analyzing the obtained results is also presented.

Macroeconomic Aggregates and Retention Ratio of Quoted Firms in Nigeria

This study examined the effects of macroeconomic aggregate on retention ratio of selected quoted manufacturing firms in Nigeria for the period 1981 to 2014. The study used secondary data. The technique adopted is the Ordinary Least Squares, Error correction mechanism and Autoregressive Distributed Lag (ARDL) Bounds approach to cointegration. The dynamic short-run estimate revealed that interest rate exerts a negative influence on retention ratio. The study also found that oil price exerts a positive and significant impact on retention ratio. Further, it revealed that capital market development exerts a positive influence on retention ratio, but financial sector's development showed a positive relationship with retention ratio, inflation rate appeared with an expected negative sign. Foreign exchange rate showed a positive relationship with retention ratio; money supply exhibited a positive influence on retention ratio of quoted firms in Nigeria. The error correction coefficients were significant with the expected sign. A long run relationship among the variables was established. Thus, the study concludes that macroeconomic variables have a significant influence on dividend policy. We recommend the need for firms to consider the operating macroeconomic framework in formulating dividend policy.

Dynamic effects of rising oil prices on consumer energy prices in Canada and the United States: Evidence from the last half a century

This paper examines the dynamic relationship between the price of crude oil and the CPI energy price sub-index in Canada and the U.S. using a Markov-regime switching model and the Bai–Perron sequential method. Since these two series are cointegrated during the sample period (January 1961–June 2013), a short-run dynamic model is thus estimated for each country in which all coefficients and the error-variance terms can freely switch over time between two values prevailing in Regimes 0 and 1. Previous studies indicate that the price of crude oil does not currently affect the aggregate CPI as much as it did in the 1970s. This finding is not disputed in this paper. However, the sequentially-determined break date as well as the time-varying regime-switching probabilities point to two new findings. First, the marginal effects of changes in oil price on consumer energy prices (not the aggregate CPI) have consistently increased and become more instantaneous for both countries after the Western U.S. Energy Crisis of 2000. Second, the speed of adjustment (proxied by different error-correction coefficients) has also risen, particularly for the U.S. Therefore, oil prices exert far more positive and immediate impacts on energy costs in the post- rather than pre-1999 periods.

Comparison and improvements of optimization methods for gas emission source identification

Identification of gas leakage source term is important for atmosphere safety. Optimization is one useful method to determine leakage source parameters. The performances of different optimization methods, including genetic algorithm (GA), simulated annealing (SA), pattern search (PS) method, Nelder–Mead simplex method (N–M simplex) and their hybrid optimization methods, were discussed. It was seen that GA–PS hybrid optimization has the best performance for location and source strength estimation while the hybrid methods with N–M simplex is the best one when time cost and robustness are added into consideration. Moreover, the performances of these optimization methods with different initial values, signal noise ratios (SNR), sensor numbers and sensor distribution forms were discussed. Further, experiment data test showed that the less deviation of forward simulation model from the real condition, the better performance of the source parameters determination method is. When two error correction coefficients were added to the Gaussian dispersion model, the accuracy of source strength and downwind distance estimation is increased. Other different cost functions were also applied to identify the source parameters. Finally, a new forward dispersion model based on radial basis function neural network and Gaussian model (Gaussian–RBF network) was presented and then it was applied to determine the leakage source parameters. The results showed that the performance of optimization method based on Gaussian–RBF network model is significantly improved, especially for location estimation. Therefore, the optimization method with a good selection of forward dispersion model and cost function will obtain a satisfactory estimation result.

Public expenditures and the unemployment rate in the American states: panel evidence

We reexamine the Unemployment Rate (UR) – government expenditure nexus in a panel of 50 State and Local Governments (SLGs) over the period 1977–2006 to provide new pre-recession empirical evidence that helps put the expectations on the effects of the federal relief to SLGs in a broader context. We found that: (1) per capita real public spending (total and capital, assistance and subsidies, wages and salaries, and social insurance categories) was part of a cointegrating relationship with UR and real per capita state personal income. (2) With the exception of social insurance, other spending variables, when statistically significant, actually had a depressing effect on UR. The magnitude of this effect, however, was generally small. UR was most sensitive to increases in wages and salaries. (3) Long-term causality analysis based on panel error-correction coefficients provided consistent evidence of a causal effect from spending to UR, but less consistent evidence of such effect in the opposite direction. Social insurance, however, drove UR. (4) The size of the error-correction coefficients suggested a slow response of UR to deviations from the cointegrating relationship. (5) The marginal effect of spending on UR increased with the amount of the federal grants received. Our results suggest that public spending may not serve as a quick fix in relation to UR. They also seem to favour allocation of the federal funds to wage and salaries and assistance and subsidies, but not to capital and social insurance expenditures to lower UR.

Industrial structure and oil consumption growth path of China: Empirical evidence

The relationships between industrial structure and the respective growth paths of oil consumption of the primary, secondary, and tertiary industries in China are examined. Based on the results, the degrees of grey correlations between total oil consumption and output values of the primary and secondary industries in China have declined, whereas that between Chinese oil consumption and output values of tertiary industries has increased. Using the VECM (vector-error correction model), the long and short run relationships between oil consumption and the three types of industries are identified. From 1978 to 2009, the long-run elasticity of total oil consumption with respect to the output value of tertiary industries ranked first, followed by the secondary industries. The negative effects of the primary industries on total oil consumption result from the "crowding out effects" of the two other industries. Although the error correction coefficients are small, the short-term impacts of the inhibition of oil consumption are limited, and China's oil consumption growth shows strong continuity and inertia. Causal tests and cointegration show that output values of the three types of industries Granger cause total oil consumption in the long run but not in the short run.

Financial development and economic growth: evidence from the European Union

PurposeThe purpose of this paper is to detect the relationship between finance and growth in the European Union countries, by searching the direction of causations.Design/methodology/approachThe growth of real sector is expressed by real GDP per capita growth (dgdpcap), while the size of the financial system by the ratio of domestic credit to GDP (domcregdp). The deposit rate and inflation are used as indexes of monetary policy. This paper estimates vector autoregressive models, based on the Akaike information criterion (AIC) and the Schartz criterion (SC) criteria and cointegration tests are conducted. To test for stationarity, the paper uses Im, Pesaran and Shin (IPS) test. In case with variables are integrated of order one I(1), the paper tests whether they are cointegrated using Pedroni's methodology.FindingsIn the short run, the size of the financial system does not directly seem to affect growth, although its increase seems to lead to an increase in the deposit rate and consequently to a decrease in real GDP per capita. However, according to the vector error correction estimates, the significance of the error correction coefficients implies that there is a relationship between real sector, financial sector and monetary policy in the long run.Originality/valuePedroni's methodology, which allows for heterogeneity across members and residual serial correlation, is used for the first time, in Europe, regarding the above‐mentioned variables. According to the results, there seems to be a long‐term relationship, between finance, growth and monetary policy.

Analysis of export demand for Ghana's timber products: A multivariate co-integration approach

This study analyzed the factors that affect the export demand for Ghana's timber products. Export demand functions and error correction models for sawnwood, plywood, and veneer using data from 1961 to 2006 were estimated. Six categories of explanatory variables were hypothesized to determine export demand: world price of wood products, income of importing countries, Ghana's external debt, exchange rates, time-related variables, and policy changes (log export ban, reduction in annual allowable cut and the imposition of export levy on air-dried sawnwood). All variables except external debt were determined from augmented Dickey–Fuller unit root tests to be integrated of order one. The Johansen multivariate cointegration test showed that there was only one cointegration relationship in each timber product data. Exchange rates and income were significant determinants of exported timber products and had the theoretically expected positive signs. The three policy initiatives significantly reduced the exports of sawnwood, but increased the exports of plywood and veneer. Price was moderately elastic for sawnwood and plywood and had the expected negative signs in both cases, while it was positive and inelastic for veneer. The error-correction coefficients show that 68% of shocks to veneer exported is corrected in the following year, while only approximately 20% and 19% of this are corrected for sawnwood and plywood, respectively. Sawnwood and plywood face stiff competition in the international market and this has revenue and tax policy implications for Ghana's forestry sector. Policies that encourage domestic processing and restrictions on both legal and illegal harvesting would work to ensure greater value-added benefits to, and sustainable forest management in, Ghana.

Information contents misjudged: Digressive convergence to equilibrium in cointegrated prices

The spot price on the Taiwan stock index is richer in information than the futures price judged by the price discovery measures of Gonzalo and Granger [Gonzalo, J., & Granger, C.W.J. (1995). Estimation of common long-memory components in cointegrated systems. Journal of Business and Economic Statistics, 13, 27–35.] and Hasbrouck [Hasbrouck, J. (1995). One security, many markets: Determining the contributions to price discovery. Journal of Finance, 50, 1175–1199.]. What is special about the markets is that both the spot and futures error-correction coefficients are positive, implying a digressive convergence to their long-run equilibrium in the error-correction (EC) process. Innovation accounting suggests that the cause of this digressive equilibrium adjustment is that investors systematically overreact to news in the less informative futures market but under-react to the more informative spot market. Our contribution is in identifying the digressive convergence implied by same-sign EC coefficients, comparing it to the normal convergence widely found in opposite-sign EC models, and providing short-run mispricing interpretations for both types of convergence to equilibrium.

The dynamics of a nonlinear relationship between crude oil spot and futures prices: A multivariate threshold regression approach

This paper segments daily data from January of 1986 to April of 2007 into three periods based on certain important events. Both periods I and II indicate that the spot prices in general are higher than futures prices as was well-known in the literature. Only period-III (2001/9/11–2007/4/30) displays a reverse phenomenon: futures prices, in general, exceed spot prices. When the absolute value of a basis (futures-spot) is greater than the threshold value in the arbitrage area (regime 1 and 3), at least one of the error correction coefficients, representing adjustment towards equilibrium, is statistically significant. That is, there exists a tendency in the oil market in which prices move toward equilibrium. With respect to the short-run dynamic interaction between spot price change (Δ s t ) and futures price change (Δ f t ), our results indicate that when the spot price is higher than futures price, and the basis is less than certain threshold value (regime 3), there exists at least one causal relationship between Δ s t and Δ f t . Conversely, when the futures price is higher than spot price and the basis is higher than certain threshold value (regime 1), there exists at least one causal relationship between Δ s t and Δ f t . Finally, we use the method suggested by Diebold and Mariano [Diebold, Francis X., Mariano, Roberto S., 1995. Comparing predictive accuracy. Journal of Business and Economic Statistics 13 (3), 253–263] to compare the predictive power between the linear and nonlinear models. Our empirical results indicate that the in-sample prediction of the nonlinear model is clearly superior to that of the linear model.

05/01599 The residential demand for electricity in Australia: An application of the bounds testing approach to cointegration

This paper reports estimates of the long- and short-run elasticities of residential demand for electricity in Australia using the bounds testing procedure to cointegration, within an autoregressive distributive lag framework. In the long run, we find that income and own price are the most important determinants of residential electricity demand, while temperature is significant some of the time and gas prices are insignificant. Our estimates of long-run income elasticity and price elasticity of demand are consistent with previous studies, although they are towards the lower end of existing estimates. As expected, the short-run elasticities are much smaller than the long-run elasticities, and the coefficients on the error-correction coefficients are small consistent with the fact that in the short-run energy appliances are fixed.

The residential demand for electricity in Australia: an application of the bounds testing approach to cointegration

This paper reports estimates of the long- and short-run elasticities of residential demand for electricity in Australia using the bounds testing procedure to cointegration, within an autoregressive distributive lag framework. In the long run, we find that income and own price are the most important determinants of residential electricity demand, while temperature is significant some of the time and gas prices are insignificant. Our estimates of long-run income elasticity and price elasticity of demand are consistent with previous studies, although they are towards the lower end of existing estimates. As expected, the short-run elasticities are much smaller than the long-run elasticities, and the coefficients on the error-correction coefficients are small consistent with the fact that in the short-run energy appliances are fixed.

Mean spillover effects in agricultural prices: The case of Greece

AbstractThis article investigates the behavior of agricultural input prices, agricultural output prices, and retail food prices using the cointegration/error–correction methodology. The findings support “cost push” and “demand pull” theories, because disequilibrium at the input level is transmitted to the retail level, and vice versa, through the output level. The estimated error–correction coefficients and price responses indicate, first, imperfect price transmission among agricultural input, output, and retail food prices, and second, that agricultural output prices are more flexible than agricultural input and retail food prices. [EconLit citations: Q110; Q130]. © 2003 Wiley Periodicals, Inc. Agribusiness 19: 425–437, 2003.

On the Estimation of the Consumption-Wealth Ratio: Cointegrating Parameter Instability and its Implications for Stock Return Forecasting

This paper investigates if the parameters of the cointegration among consumption, asset wealth, and labor income are stable over the post-war sample period. Although Lettau and Ludvigson (2001a) find that the estimated consumption-wealth ratio (CAY) is a strong predictor of aggregate stock returns, the instability of the cointegrating parameters suggests that the empirical applications of CAY are problematic. Our empirical results from subsample estimations, stability tests, error correction coefficients estimations, and rolling regressions all indicate substantial changes in the cointegrating parameter estimates over the sample period, which translates into the deteriorating forecasting power of CAY for aggregate stock returns.

Forecasting an aggregate of cointegrated disaggregates

This study examines the problem of forecasting an aggregate of cointegrated disaggregates. It first establishes conditions under which forecasts of an aggregate variable obtained from a disaggregate VECM will be equal to those from an aggregate, univariate time series model, and develops a simple procedure for testing those conditions. The paper then uses Monte Carlo simulations and an empirical example to examine how analysis of forecasting an aggregate might be affected by a failure to correct for cointegration. The Monte Carlo and empirical analyses indicate the effects of ignoring cointegration vary sharply with model parameterization. When the aggregate of the error correction coefficients is small, ignoring cointegration will not have large effects.