scholarly journals Environmental Pollution Effects of Regional Industrial Transfer Illustrated with Jiangsu, China

2021 ◽  
Vol 13 (21) ◽  
pp. 12128
Author(s):  
Guangxiong Mao ◽  
Wei Jin ◽  
Ying Zhu ◽  
Yanjun Mao ◽  
Wei-Ling Hsu ◽  
...  
Keyword(s):  
Environmental Pollution ◽  
Manufacturing Industry ◽  
Time Series Data ◽  
Estimation Method ◽  
Raw Material ◽  
Series Data ◽  
Pollution Load ◽  
Pollution Effects ◽  
Industrial Transfer ◽  
Southern Jiangsu

Industrial transfer is reshaping the geographic layout of industries and facilitating the transfer and spread of environmental pollution. This study employs the pollution transfer estimation method to discuss the environmental effect of industrial transfer. By compiling statistics on industries of a certain scale according to time-series data, the researchers compute the pollution load generated by industrial transfer and the difference in pollution emissions for each region and industry. Through the constructed evaluation model, the empirical scope is Jiangsu, which is the most developed industry in China. The results reveal that there is an apparent spatial hierarchy among the transferred industries in Jiangsu. Most industries transfer from the southern Jiangsu region toward the central Jiangsu and northern Jiangsu regions. Environmental pollution is redistributed among prefecture-level cities because of intercity industrial transfer; the spatial characteristics of pollution exhibit a notable hierarchical pattern. Furthermore, the transferred pollution load differs considerably between industries. The textile industry and chemical raw material and chemical product industry are mainly transferred toward the Central Jiangsu and Northern Jiangsu regions, whereas the papermaking and paper product manufacturing industry is primarily redistributed to the Southern Jiangsu region. The empirical results can serve as a reference for analyzing the environmental pollution effects of regional industrial transfer.

scholarly journals PERMINTAAN JAGUNG SEBAGAI BAHAN BAKU INDUSTRI PAKAN TERNAK DI INDONESIA

Agro Ekonomi ◽  
2017 ◽  
Vol 15 (1) ◽  
pp. 1
Author(s):  
Diah Ariyanti ◽  
Any Suryantini ◽  
Masyhuri Masyhuri
Keyword(s):  
Time Series Data ◽  
Import Price ◽  
Least Square ◽  
Raw Material ◽  
Series Data ◽  
Domestic Price ◽  
Ordinary Least Square ◽  
Feed Industry ◽  
Soybean Cake ◽  
Good For

The objectives of this research are to know the factors influencingdomestic maize demand, import maize demand, and total maize demand asraw material for feed industry in Indonesia, also their trend at five yearslater. The research use time series data. during 1976-2004. Simultaneousequations used to analyze domestic and import maize demand as rawmaterial for feed industry in Indonesia, while ordinary least square (OLS)used to analyze total maize demand as raw material for feed industry inIndonesia. The results show that domestic maize demand influenced negatively by maize domestic price and influenced positively by soybean cake import price, and trend of time. Cowpopulation, maize import price, and soybean cake import price influence import maize demand negatively, while fowl population and trend of time influence import maize demand positively. Total maize demand for feed industry in Indonesia positively influenced by soybean cake import price and cow population, and negatively influenced by maize domestic price. Soybean cake iscomplementary good for domestic maize and total maize, but becomesubstitution good for import maize. The trend of maize demand, includingdomestic and import maize demand, as raw material for feed industry inIndonesia increasing in the future.

Democratic peace: Does ethnic inclusiveness reduce interstate conflict?

2019 ◽  
pp. 019251211988473
Author(s):  
Seung-Whan Choi ◽  
Henry Noll
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Estimation Method ◽  
Interstate Conflict ◽  
Model Specification ◽  
Series Data ◽  
Democratic Peace ◽  
Interstate Disputes ◽  
Time Series Data Analysis ◽  
Cross National

In this study, we argue that ethnic inclusiveness is an important democratic norm that fosters interstate peace. When two states are socialized into the notion of ethnic tolerance, they acquire the ability to reach cooperative arrangements in time of crisis. Based on cross-national time-series data analysis covering the period 1950–2001, we illustrate how two states that are inclusive of their politically relevant ethnic groups are less likely to experience interstate disputes than states that remain exclusive. This finding was robust, regardless of sample size, intensity of the dispute, model specification, or estimation method. Therefore, we believe in the existence of ethnic peace: ethnic inclusiveness represents an unambiguous force for democratic peace.

Changepoint Analysis of Binary and Ordinal Probit Models: An Application to Bank Rate Policy Under the Interwar Gold Standard

2011 ◽  
Vol 19 (2) ◽  
pp. 188-204 ◽  
Author(s):  
Jong Hee Park
Keyword(s):  
Time Series ◽  
Gold Standard ◽  
Time Series Data ◽  
Likelihood Function ◽  
Marginal Likelihood ◽  
Estimation Method ◽  
Simulated Data ◽  
Likelihood Method ◽  
Series Data ◽  
Ordinal Probit

In this paper, I introduce changepoint models for binary and ordered time series data based on Chib's hidden Markov model. The extension of the changepoint model to a binary probit model is straightforward in a Bayesian setting. However, detecting parameter breaks from ordered regression models is difficult because ordered time series data often have clustering along the break points. To address this issue, I propose an estimation method that uses the linear regression likelihood function for the sampling of hidden states of the ordinal probit changepoint model. The marginal likelihood method is used to detect the number of hidden regimes. I evaluate the performance of the introduced methods using simulated data and apply the ordinal probit changepoint model to the study of Eichengreen, Watson, and Grossman on violations of the “rules of the game” of the gold standard by the Bank of England during the interwar period.

Impact of Fiscal Policy on Agricultural Output in Nigeria

2019 ◽  
Vol 9 (7) ◽  
pp. 1428 ◽  
Author(s):  
Adedoyin Isola LAWAL ◽  
Ernest Onyebuchi FIDELIS ◽  
Abiola Ayoopo BABAJIDE ◽  
Barnabas O. OBASAJU ◽  
Oluwatoyese OYETADE ◽  
...  
Keyword(s):  
Fiscal Policy ◽  
Agricultural Sector ◽  
Time Series Data ◽  
Negative Impact ◽  
Capital Expenditure ◽  
Research Work ◽  
Estimation Method ◽  
Series Data ◽  
Agricultural Output ◽  
The Impact

This study examines the impact of fiscal policy on agricultural output in Nigeria using the most recent official data. The metrics for fiscal policy is government capital expenditure and custom duties on fertilizer. The study used annual time series data obtained from CBN annual statistical bulletin, NCS, and FIRS which was found to be stationary at the order of I(1) and I(0). The order of unit root test led to the use of ARDL estimation method employed in the empirical analysis of this research work. The study found evidence of both short and long run relationship between the variables (VAO, GEX, IDMF, and ACGSF) using both Johansen co-integration and ARDL Bounds test. Although government expenditure (GEX) to agricultural sector was found to be statistically insignificant which recommend that government should increase agriculture capital expenditure to ensure that its contribution is significant. Consequently, custom duties on fertilizer (IDMF) was found to be negatively signed and significant indicating a negative impact on agricultural output. This demands that the policy makers should be prudent in the use of fiscal policy instrument in achieving its desired objective.

scholarly journals Cuffless Blood Pressure Estimation Based on Data-Oriented Continuous Health Monitoring System

2017 ◽  
Vol 2017 ◽  
pp. 1-10 ◽  
Author(s):  
Kengo Atomi ◽  
Haruki Kawanaka ◽  
Md. Shoaib Bhuiyan ◽  
Koji Oguri
Keyword(s):  
Blood Pressure ◽  
Time Series Data ◽  
Estimation Method ◽  
Series Data ◽  
Healthy Life ◽  
Blood Pressure Data ◽  
Pressure Estimation ◽  
Blood Pressure Estimation ◽  
Cuffless Blood Pressure ◽  
Lifestyle Related Diseases

Measuring blood pressure continuously helps monitor health and also prevent lifestyle related diseases to extend the expectancy of healthy life. Blood pressure, which is nowadays used for monitoring patient, is one of the most useful indexes for prevention of lifestyle related diseases such as hypertension. However, continuously monitoring the blood pressure is unrealistic because of discomfort caused by the tightening of a cuff belt. We have earlier researched the data-oriented blood pressure estimation without using a cuff. Remarkably, our blood pressure estimation method only uses a photoplethysmograph sensor. Therefore, the application is flexible for sensor locations and measuring situations. In this paper, we describe the implementation of our estimation method, the launch of a cloud system which can collect and manage blood pressure data measured by a wristwatch-type photoplethysmograph sensor, and the construction of our applications to visualize life-log data including the time-series data of blood pressure.

scholarly journals A Time-Varying Coupling Analysis of Expressway Traffic Volume and Manufacturing PMI

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Shuo Sun ◽  
Mingchen Gu ◽  
Yingping Wang ◽  
Rongjie Lin ◽  
Lifeng Xing ◽  
...  
Keyword(s):  
Manufacturing Industry ◽  
Time Series Data ◽  
Traffic Volume ◽  
Series Data ◽  
Time Varying ◽  
Truck Traffic ◽  
Positive Interaction ◽  
Vector Autoregressive ◽  
Coupling Relationship ◽  
Johansen Cointegration Test

This study investigates the time-varying coupling relationship between expressway traffic volume and manufacturing purchasing manager index (PMI). First, for the traffic volume and manufacturing PMI time-series data, unit root stability test and Johansen cointegration test are applied to determine the stability of single sequence and the long-term stable correlation between variables, respectively. Then, a time-varying vector autoregressive model (TVP-VAR) is developed to quantify the time-varying correlation between variables. The time-varying parameters of TVP-VAR are estimated using the Markov chain Monte Carlo (MCMC) theory. Finally, the model is validated using examples from China. In the numeric example, three variables, i.e., expressway car traffic volume, expressway truck traffic volume, and manufacturing PMI, are selected for analysis. Results show that there is a positive interaction between expressway traffic volume (both car and truck) and manufacturing PMI. Express traffic volume slowly promotes the development of manufacturing industry. However, with the reform policy of road freight structure in China, the promotion effect of truck traffic on manufacturing PMI in the past two years has decreased significantly. Moreover, as affected by the China demand-led economic development model in recent years, the stimulus effect of manufacturing PMI on expressway passenger traffic volume has increased year by year. And, while the expressway freight structure remains stable, truck traffic volume is hardly affected by fluctuations in manufacturing PMI. These research results are helpful for policy makers to understand the time-varying coupling relationship between expressway traffic volume and manufacturing development and finally to improve the expressway management level.

THE INDONESIAN AGRICULTURAL PERFORMANCES UNDER CHINA-ASEAN FREE TRADE AREA: GO UP OR GO DOWN? Case of Agriculture Raw Material and Food Product

2017 ◽  
Vol 1 (1) ◽  
Author(s):  
Nasrudin Nasrudin ◽  
Budiyanto Budiyanto
Keyword(s):  
Free Trade ◽  
Economic Integration ◽  
Agricultural Sector ◽  
Time Series Data ◽  
Positive Impact ◽  
Raw Materials ◽  
Food Product ◽  
Raw Material ◽  
Series Data ◽  
The Impact

As an agricultural country, the Indonesian agricultural sector should obtain a positive impact of the regional economic integration. Since in 2004 by the Early Harvest Program (EHP) of China-ASEAN Free Trade Agreement (CAFTA), most agricultural commodities have lowered tariff, indeed some have been zero percent.Unfortunately, the performance of the agricultural sector has not shown tangible improvement. Then beforethe rates was released for all commodities, should be evaluated and re-defined policies that should be taken. This paper purposesto examine the impact of the implementation of CAFTA on the Indonesian agricultural performances. The objectives will be achieved by compare the performance preand post-CAFTA; predict the performance if CAFTA is fully implemented, by performing simulations and econometric models. By using time series data 1990-2011, agriculture can be divided into two categories; agricultural raw materials and food products. The estimation result of econometric modeling by simultaneous equations, the Indonesian agricultural sector performance after CAFTA is not better than before implementation. Predicted will decrease when the entire rates later free. Keywords: agriculture raw material; foods product; agriculture performance; economic integration

scholarly journals Tracking Poisson Parameter for Non-Stationary Discontinuous Time Series with Taylor’s Abnormal Fluctuation Scaling

Stats ◽  
2019 ◽  
Vol 2 (1) ◽  
pp. 55-69 ◽  
Author(s):  
Gen Sakoda ◽  
Hideki Takayasu ◽  
Misako Takayasu
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
State Space Model ◽  
Estimation Method ◽  
Stationary Time Series ◽  
Series Data ◽  
Large Fluctuations ◽  
Taylor’S Law ◽  
Fluctuation Scaling ◽  
Poisson Parameter

We propose a parameter estimation method for non-stationary Poisson time series with the abnormal fluctuation scaling, known as Taylor’s law. By introducing the effect of Taylor’s fluctuation scaling into the State Space Model with the Particle Filter, the underlying Poisson parameter’s time evolution is estimated correctly from given non-stationary time series data with abnormally large fluctuations. We also developed a discontinuity detection method which enables tracking the Poisson parameter even for time series including sudden discontinuous jumps. As an example of application of this new general method, we analyzed Point-of-Sales data in convenience stores to estimate change of probability of purchase of commodities under fluctuating number of potential customers. The effectiveness of our method for Poisson time series with non-stationarity, large discontinuities and Taylor’s fluctuation scaling is verified by artificial and actual time series.

An econometric study of carbon dioxide (CO2) emissions, energy consumption, and economic growth of Pakistan

2012 ◽  
Vol 6 (4) ◽  
pp. 518-533 ◽  
Author(s):  
Matloub Hussain ◽  
Muhammad Irfan Javaid ◽  
Paul R. Drake
Keyword(s):  
Economic Growth ◽  
Carbon Dioxide ◽  
Energy Consumption ◽  
Environmental Pollution ◽  
Granger Causality ◽  
Time Series Data ◽  
Series Data ◽  
Future Research ◽  
Content Type ◽  
Per Capita

PurposeThe purpose of this paper is to examine the relationship among environmental pollution, economic growth and energy consumption per capita in the case of Pakistan. The per capital carbon dioxide (CO2) emission is used as the environmental indicator, the commercial energy use per capita as the energy consumption indicator, and the per capita gross domestic product (GDP) as the economic indicator.Design/methodology/approachThe investigation is made on the basis of the environmental Kuznets curve (EKC), using time series data from 1971 to 2006, by applying different econometric tools like ADF Unit Root Johansen Co‐integration VECM and Granger causality tests.FindingsThe Granger causality test shows that there is a long term relationship between these three indicators, with bidirectional causality between per capita CO2 emission and per capita energy consumption. A monotonically increasing curve between GDP and CO2 emission has been found for the sample period, rejecting the EKC relationship, implying that as per capita GDP increases a linear increase will be observed in per capita CO2 emission.Research limitations/implicationsFuture research should replace the economic growth variable, i.e. GDP by industrial growth variable because industrial sector is major contributor of pollution by emitting CO2.Practical implicationsThe empirical findings will help the policy makers of Pakistan in understanding the severity of the CO2 emissions issue and in developing new standards and monitoring networks for reducing CO2 emissions.Originality/valueEnergy consumption is the major cause of environmental pollution in Pakistan but no substantial work has been done in this regard with reference to Pakistan.

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