Cochrane-Orcutt Procedure Research Articles

Does Shanghai International Financial Center Promote RMB Internationalization?

The construction of the Shanghai International Financial Center was completed in 2020, which signaled the new age of financial reforms in China. The Shanghai International Financial Center plays a significant part in the progress of RMB internationalization. However, empirical proof of the impacts remains few. So, we conducted an empirical analysis to determine if the Shanghai International Financial Center promoted RMB internationalization effectively. To obtain robust results, we conducted regressions with Newey–West standard errors, Cochrane–Orcutt estimation, and Prais–Winsten estimation. We observed that the Shanghai International Financial Center has significant positive effects on RMB internationalization by expanding financial scale and activity. The findings give adequate evidence to support the theories advanced in prior research, and the methodology and indicators used in the study may serve as a guide for future research. We made several policy discussions of the findings regarding the continued expansion of the offshore market and capital liberalization within Shanghai.

Relationships of Wheat, Dry Bean and Chickpea Yields with Global Climate Change in Suşehri District, Turkey

The long-term impact of atmospheric events is defined as climate. Agricultural activities are more affected by climate change since they mostly rely on nature. Agricultural activities may also induce climate change. Therefore, it is valuable to know how agricultural activities are affected by climate change. Therefore, this study was conducted to assess long-term changes in climate and agricultural products and mutual relationships between them in the Suşehri district of Sivas province located in the Kelkit Basin. Climate (air temperature, precipitation, and relative humidity) and yield (crops of wheat, dry bean, and chickpea) data of the 1991 – 2017 period were used. Long-term temporal changes were tested with the nonparametric Mann-Kendall trend test. Relationships were analyzed with the use of the Cochrane-Orcutt estimation regression. The air temperature showed increasing tendency both annually and seasonally, and also had negative effects on wheat yield. Relative humidity showed a positive relationship with the wheat yields both annually and seasonally. Any climate data did not have a significant effect on chickpea and dry bean yields. If the temperature increase continues in the future, negative effects of climate change on agricultural products of the region will be inevitable. It is likely that agriculture in the region will shift to higher altitudes in time. Present findings could be used for the entire Kelkit Basin, which is located in the same climate and geographical zone as Suşehri district.

A Study on the Optimal Ratio of Research and Development Investment in the Energy Sector: An Empirical Analysis in South Korea

The necessity for energy research and development (ER&D) is increasing as greenhouse gases and climate change are becoming global issues. To support sustainable economic growth through ER&D, it is necessary to examine the optimal ratio of ER&D investment to total R&D investment to maximize economic growth. However, there are no studies on the appropriate level of ER&D in total R&D investment for economic growth. This study attempts to empirically estimate the optimal ratio of ER&D investment to maximize gross domestic product (GDP) in South Korea. We utilized the Cobb-Douglas production function for our econometric model and corrected the autocorrelation problem using the Cochrane-Orcutt iterative procedure. Our results showed that both, ER&D and non-ER&D have positive correlations with GDP. The optimal ratio of ER&D is derived as 13.23%, which indicates that the current ratio of Korean ER&D should be revised upward. Further, ER&D investment in the private sector needs to be increased to achieve the optimal ratio because the current statistics in Korea describes that private companies in the energy industry invest much less in R&D than the government. Based on the results, we suggest government strategies to enhance ER&D investment in the private sector as well as the public sector.

Daily coal mining as a factor influencing methane concentration at a longwall – a case study

This paper describes an exemplary method of presenting the average concentration of methane at the outlet of one of walls in the “Krupiński” mine. This method involves the linear function of current mining and mining on preceding days. The ordinary least squares method used to determine parameters of that function was found to produce too serious errors. Therefore, it is recommended to use one of generalised least squares method. In this case Cochrane-Orcutt estimation for the generalised least squares method was applied. Measured and approximated values of methane concentration showed good compliance. Also, parameters of the approximation function for the average concentration of methane was determined. It was a linear function of the square root of mining on the current day and the preceding days. For that purpose, Cochrane-Orcutt procedure was also applied. Results from approximation by mentioned functions were nearly identical.

ANALYSIS OF THE IMPACT OF SELECTED ECONOMIC VARIABLES ON SORGHUM PRICES IN NIGERIA

Nigeria is the world’s leading producer of sorghum intended for use as food grain. Likewise, there has been growing industrial demand for sorghum in the livestock breeding and brewery sectors. As sorghum prices have been on the increase, it becomes pertinent to identify the determinants of this development in order to nip the imminent food crisis in the bud. This study relied on time series data spanning from 1970 to 2015 retrieved from FAOSTAT and World Bank databases. Analytical methods employed include the unit root test, cointegration test and error correction mechanism. The diagnostic tests indicated the presence of autocorrelation which was subsequently adjusted with the Cochrane-Orcutt procedure. Subsequent tests indicated that variables fit well to the model. As shown by the ADF unit root test, the modeled variables were non-stationary but became stationary after first differencing. At a significance level of 5%, the sorghum price was determined by gross domestic product (GDP), annual money supply, official exchange rate and crude oil price, both in the long and short run, whereas the lagged price of sorghum also had an effect on prices in the short run. The study recommends that macroeconomic variables such as GDP, annual money supply and official exchange rate be taken cognizance of when planning the agricultural development in Nigeria.

Improved CENA Regression Relationships between Modified Mercalli Intensities and Ground‐Motion Parameters

Abstract Comparisons between peak ground motions (PGMs) and intensities are mainly based on the regression of felt intensity with peak ground acceleration (PGA), peak ground velocity (PGV), response spectral values, and occasionally with maximum displacement. Using the Next Generation Attenuation‐East database, we update and extend the relations of Dangkua and Cramer (2011). We start by developing magnitude and distance‐independent linear regression relationships between modified Mercalli intensity (MMI) in the range of I≤MMI≤VII and the ground‐motion parameters (GMPs) of PGA, PGV, and 21 pseudospectral accelerations for central and eastern North America (CENA). We correct for recently acknowledged differences between community Internet intensities (CIIs) and MMI (Hough, 2013, 2014; Boyd and Cramer, 2014; Tosi et al. , 2015). We then perform residual analysis to evaluate whether there are any discrepancies and dependency, first with magnitude and then distance. For the magnitude‐dependent analysis, we use a bilinear fit. This bilinear magnitude dependence is especially important for longer periods. The residuals show homoskedasticity with zero mean and are serially correlated. We correct for the serial correlation using the Cochrane–Orcutt procedure. Our new ground‐motion intensity correlation equations for CENA have the form log 10 ( Y )= c 1 + c 2 × I + c 3 ×min{ M w , M t }+ c 4 ×log 10 (Dist), in which log 10 ( Y ) is the GMP, M w is the moment magnitude, M t is the magnitude of the bend in the bilinear magnitude dependence, log 10 (Dist) is the distance term, I is the intensity of interest (MMI or CII), and c 1 , c 2 , c 3 , and c 4 are the coefficients of regression. The equation is invertible for obtaining both CII and MMI from the PGM of interest and vice versa. Electronic Supplement: Figures of data for intensity prediction equation (IPE) evaluation, additional residual analyses, and evaluations based on other performance metrics. Tables that list the events and details of the earthquakes used in the analysis and the means, standard errors, and standard deviations of modified Mercalli intensity (MMI)/community Internet intensity (CII) values of the selected ground‐motion parameters.

Structure and Performance of Indian Organised Manufacturing Industries during Pre and Post Reform Period

Present study is investigating growth pattern and productivity trends in Indian organised manufacturing industries for the period of 1973–74 to 2011–12 by making use of ASI time series data. The growth of Indian organised manufacturing industries has been estimated in terms of five variables. Yearly and CAGR have been worked out and partial factor productivity was estimated to ascertain the impact of NIP on growth of organised manufacturing industries. This study used transformed Cochrane-Orcutt iterative and Prais-Winsten Procedure to overcoming the problem of auto correlation for estimating the relationship between labour productivity, capital intensity and real wage in the Indian organised manufacturing industries by fitting multiple regression models. The present study found that in post-reform era growth rate decreased in number of factories, employment and total emoluments whereas growth rate increased in gross fixed capital and gross value added. This represent that the post-reform has promoted the use of capital intensive and labour saving techniques of production leading to poor growth of employment, total emoluments and it has also facilitated the elimination of sick factories in Indian organised manufacturing industries. The comparative profile of pre-reform and post-reform period revealed that during reform period productivities of labour declined but capital productivity decelerated significantly whereas capital intensity and real wage improved significantly. Co-efficient of capital intensity is found to be statistically significant at 1% level of significance while the co-efficient of real wage was found to be statistically insignificant which means that increase in labour productivity in the Indian organised manufacturing industries was explained by the increase in capital intensity rather than the increase in real wage during the period under study.

Comparison and Validation of Selected Evapotranspiration Models for Conditions in Poland (Central Europe)

The FAO-56 Penman-Monteith (PMF56) model is accepted as the standard method for estimating reference crop (grass) evapotranspiration. However, poor data availability limits the use of this method in many regions. This study aimed to overcome this limitation (1) by evaluating the goodness-of-fit of selected simple evapotranspiration methods in relation to the PMF56 model and (2) by adjusting four of these models and developing a multiple regression equation for conditions in Poland using the PMF56 model as a reference. Using daily meteorological data, four simple models were calibrated by the generalised reduced gradient (GRG) method; moreover, a multiple regression equation was developed on the basis of Cochrane-Orcutt estimation because the error term of the ordinary least squares model was autocorrelated. When radiation data were lacking and sunshine duration data were available, the PMF56 method with a calibrated Ångström-based estimation of solar radiation was the most accurate method (relative error, RE = 0.096, for Sulejów). When neither radiation nor sunshine duration data were included in the dataset, the calibrated Penman method performed best (RE = 0.254). Moreover, when only temperature or pan evaporation data were available, the calibrated Hargreaves method provided the most accurate results (RE = 0.275). Much poorer results were obtained using the calibrated pan coefficient method (RE = 0.435). Ultimately, we developed a multiple regression method in this study that exhibited good performance (RE = 0.170). Taking into account the data limitations, the methods calibrated in this study are recommended for estimating evapotranspiration in Central Europe. This approach would substantially decrease the errors produced by the recommended non-calibrated equations.

Monetary dynamics in post inflation Bolivia

Is inflation always explained as a monetary phenomenon? In this study, the author presents empirical evidence regarding the relation of Money Growth and its effect on Inflation, for the specific case of Bolivia. The text describes the situation of the country analyzed in terms of monetary policy after one of the worst cases of hyperinflation ever; empirical evidence is presented trough two independent estimations, one following the Cochrane-Orcutt procedure, and the other following a Box-Jenkins procedure (ARMA process) that confirms the relation between Money Growth and Inflation in Bolivia using data for the years 1998 to 2010.

IT산업 연구개발 투자의 경제적 효과 분석

본 연구에서는 IT산업의 연구개발 투자가 부가가치에 미치는 영향을 분석하기 위하여 IT산업을 방송통신기기, 정보기기, 전자부품으로 세분하고, 각 세부 산업별로 자본스톡, 노동투입, 연구개발스톡을 독립변수로 설정하여 다중회귀분석을 실시하였다. 분석 결과, 모든 산업부문에서 t-value와 R-square 값들은 유의한 것으로 나타났지만, 자기상관은 매우 높게 나타났다. 한편 정보기기산업에서는 연구개발스톡, 전자부품산업에서는 노통투입의 계수 값이 마이너스로 나타나서 다중공선성의 징후가 의심되었다. 본 연구에서는 Cochrane-Orcutt 절차와 주성분회귀분석을 통하여 자기상관 및 다중공선성의 문제를 해결하였다. 연구개발스톡이 부가가치에 미치는 영향을 분석한 결과, 방송통신기기산업의 연구개발투자가 정보기기산업이나 전자부품산업에 비해 훨씬 큰 영향을 미치는 것으로 추정되었다. This study has conducted the economic effects of R&D investment in the IT industry using multi-regression analysis with three independent variables; capital stock, labor input and R&D stock. In this study, the IT industry has been categorized into three sub-industries; broadcasting communication appliances, information appliances and electronic components industry. Our analysis has found that auto-correlation shows considerable levels whereas figures of t-value and R-square show significant levels among all the IT sub-industries. Meanwhile, the values of R&D stock in the information appliances industry and that of labor input coefficients in the electronic components industry were minus, thus multi-collinearity was suspected. We have solved the problems regarding auto-correlation and multi-collinearity through Cochrane-Orcutt estimation and principal components analysis. This paper has derived the implications that R&D investment in the broadcasting communication industry is much more influential than any other IT sub-industry.

한우브랜드의 성장과 유통마진의 관계 분석

Hanwoo, Korean cattle, is traditionally an important livestock to farmers and also important meat to consumers. Recently, to make more efficient production system and provide cheaper and high-quality hanwoo meat, the scale-up via brand is emphasized. However, the price of hanwoo is getting higher and the price increase is considered to occur due to marketing margins in the distribution process. In this study, factors affecting the hanwoo marketing margin are analyzed using 2004-2009 monthly data. In the Cochrane-Orcutt estimation of marketing margin, hanwoo production, other domestic production and import, income, output index, market share of major retailers, and market share of hanwoo brands shows statistical significance in the result. The results shows basic factors of the marketing margins to hanwoo and gives some implications to the management system of hanwoo brand like a sophisticated market segmentation and a differentiated promotion.

Money growth and inflation: evidence from post-inflation Bolivia

In this short study, the author presents empirical evidence regarding the relation of money growth and its effect on inflation, for the case of Bolivia. The text describes the situation of the country analysed in terms of monetary policy after one of the worst cases of hyperinflation ever; empirical evidence is presented through two independent estimations, one following the Cochrane-Orcutt procedure, and the other following a Box-Jenkins procedure (ARMA process) that confirms the relation between money growth and inflation in Bolivia using data for the years 1998 to 2010. Evidence confirms the impact of money growth on inflation; the evidence suggests that the level of current inflation in Bolivia has a strong relation with the level of money quantity of two past periods on average. Moreover, the results show that monetary expansion affects the level of inflation in even when controlling for time impacts. The author also tries to assess the impact that a period of high inflation has in the development of growth policies for the case of Bolivia.

Bootstrap procedures in a spatial-temporal model

Two bootstrap procedures are introduced into the hybrid of the backfitting algorithm and the Cochrane–Orcutt procedure in the estimation of a spatial-temporal model. The use of time blocks of consecutive observations in resampling steps proved to be optimal in terms of stability and efficiency of estimates. Between iterations, there were minimal changes in the empirical distributions of the parameter estimates associated with the covariate and temporal effects indicating convergence of the algorithm. Crop yield data are used to illustrate the proposed methods. The simulation study indicated that prediction error from the fitted model (estimated from either Method 1 or Method 2) is very low. Also, the prediction error is relatively robust to the number of spatial units and the number of time points.

Price response of herd off-take under market liberalization in a developing cattle sector: panel analysis applied to Kenya's ranching

ABSTRACTThe influence of price, in view of macro-economic policy change and a set of other factors, on herd off-take rates from ranches in Kenya over a period of 17 years was assessed. An AR(1) equation, based on Nerlove's classical dynamic supply model, was derived and fitted to panel data using the Cochrane–Orcutt procedure. Pooling of data was done to circumvent data insufficiency, thereby improving the statistical power of the analysis. Results indicate that price change has had a significant effect on ranch herd off-take, and climatic factors also account for long-run off-take levels.

Predicting U.S. Restaurant Sales Using the Stock Index and Disposable Income

ABSTRACT This study investigates whether stock indexes and disposable personal income can be used to predict future U.S. restaurant sales. A time-series ordinary least squares model was estimated to examine the ability of stock indexes and disposable personal income to predict future U.S. restaurant sales. The final model, established by applying the Cochrane-Orcutt transformation procedure, shows that the S&P 500 index and per capita disposable income can serve as useful leading indicators of future U.S. restaurant sales.

GRETL: Econometric software for the GNU generation

Journal of Applied EconometricsVolume 18, Issue 1 p. 105-110 Software Review GRETL: Econometric software for the GNU generation Giovanni Baiocchi, Corresponding Author Giovanni Baiocchi jb35@york.ac.uk Department of Environment, University of York, York YO10 5DD, UKDepartment of Environment, University of York, York YO10 5DD, UK.Search for more papers by this authorWalter Distaso, Walter Distaso Department of Economics, University of Exeter, Exeter EX4 4PU, UKSearch for more papers by this author Giovanni Baiocchi, Corresponding Author Giovanni Baiocchi jb35@york.ac.uk Department of Environment, University of York, York YO10 5DD, UKDepartment of Environment, University of York, York YO10 5DD, UK.Search for more papers by this authorWalter Distaso, Walter Distaso Department of Economics, University of Exeter, Exeter EX4 4PU, UKSearch for more papers by this author First published: 18 February 2003 https://doi.org/10.1002/jae.704Citations: 53Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat Citing Literature Volume18, Issue1January/February 2003Pages 105-110 RelatedInformation

Trends and spatial distribution of deaths of children aged 12-60 months in São Paulo, Brazil, 1980-98.

To describe trends in the mortality of children aged 12-60 months and to perform spatial data analysis of its distribution at the inner city district level in São Paulo from 1980 to 1998. Official mortality data were analysed in relation to the underlying causes of death. The population of children aged 12-60 months, disaggregated by sex and age, was estimated for each year. Educational levels, income, employment status, and other socioeconomic indices were also assessed. Statistical Package for Social Sciences software was used for the statistical processing of time series. The Cochrane-Orcutt procedure of generalized least squares regression analysis was used to estimate the regression parameters with control of first-order autocorrelation. Spatial data analysis employed the discrimination of death rates and socioeconomic indices at the inner city district level. For classifying area-level death rates the method of K-means cluster analysis was used. Spatial correlation between variables was analysed by the simultaneous autoregressive regression method. There was a steady decline in death rates during the 1980s at an average rate of 3.08% per year, followed by a levelling off. Infectious diseases remained the major cause of mortality, accounting for 43.1% of deaths during the last three years of the study. Injuries accounted for 16.5% of deaths. Mortality rates at the area level clearly demonstrated inequity in the city's health profile: there was an increasing difference between the rich and the underprivileged social strata in this respect. The overall mortality rate among children aged 12-60 months dropped by almost 30% during the study period. Most of the decline happened during the 1980s. Many people still live in a state of deprivation in underserved areas. Time-series and spatial data analysis provided indications of potential value in the planning of social policies promoting well-being, through the identification of factors affecting child survival and the regions with the worst health profiles, to which programmes and resources should be preferentially directed.

Some further results on the efficiency of the Cochrane–Orcutt-estimator

Abstract When the disturbances in the linear regression model are generated by a first-order autoregressive scheme the Cochrane–Orcutt (CO)-estimator is a well-known alternative to OLS- and GLS-estimator. In this paper it is analyzed in which situations the CO-estimator is worse or better than its competitors in terms of efficiency which is here defined as the ratio of the total variances.

A simple recursive estimation method for linear regression models with AR(p) disturbances

An exact transformation that reduces the AR(p) process into white noise is well known in statistics, see Fuller (1976). However, practitioners still use and econometric textbooks still recommend the Cochrane-Orcutt procedure for p>2, see Greene (1990). This paper derives an alternative exact transformation for the AR(p) process which is computationally simple. Based on this transformation, a GLS estimator is proposed, requiring only least squares regressions and recursive computations. This is illustrated for the AR(3) case.

Leverage and cochrane-orcutt estimation in linear regression

In this paper we investigate the influence of the correlation coefficient on the hat matrix diagonal component corresponding to the first transformed observation in regression models with AR(l)-errors. Furthermore a relationship between this first leverage and the efficiency of the Cochrane-Orcutt Estimator is established.