Research on the Relationship between Income and Consumption of the Urban Residents in Hunan Province on the Basis of Error Correction Model

By using error correction model, I conduct co-integration analysis on the research of the relationship between the per capita practical consumption and per capita practical disposable income of urban residents in Hunan Province from 1978 to 2009. The results show that there is a co-integration relationship between the per capita practical consumption and the practical per capita disposable income of urban residents, and based on these, the corresponding error correction model is established. Finally, corresponding countermeasures and suggestions are put forward as follows: broaden the income channel of urban residents; create goods consuming environment; perfect socialist security system.

Relationship Between Agricultural Credits and Agricultural Economy Based on Error Correct Model in Heilongjiang Province

Heilongjiang is a large agriculture province.Problems of agriculture,rural areas and farmers are urgent to be solved.The development of agriculture needs the support of agricultural credits,because finance is the center of agriculture economy.However,the low comparative advantage in agriculture and pursuit of the capital interests which aggravate the conflicts of supply and demand of agricultural funds.Lacking of fund is the main factor that constrains the development of agricultural economy.In order to analyze the economic effect of agricultural credits on agricultural economy,an error correction model was set up to research the relationship between them,which based on the least square methods.Through the study of the contribution from agricultural credits to total value of agricultural out-put,the empirical evidence for developing the rural financial vigorously was provided,in order to promote the agricultura leconomic development.

A Robust Conformer-Based Speech Recognition Model for Mandarin Air Traffic Control

This study aims to address the deviation in downstream tasks caused by inaccurate recognition results when applying Automatic Speech Recognition(ASR)technology in the Air Traffic Control(ATC)field.This paper presents a novel cascaded model architecture,namely Conformer-CTC/Attention-T5(CCAT),to build a highly accurate and robust ATC speech recognition model.To tackle the challenges posed by noise and fast speech rate in ATC,the Conformer model is employed to extract robust and discriminative speech representations from raw waveforms.On the decoding side,the Attention mechanism is integrated to facilitate precise alignment between input features and output characters.The Text-To-Text Transfer Transformer(T5)language model is also introduced to handle particular pronunciations and code-mixing issues,providing more accurate and concise textual output for downstream tasks.To enhance the model’s robustness,transfer learning and data augmentation techniques are utilized in the training strategy.The model’s performance is optimized by performing hyperparameter tunings,such as adjusting the number of attention heads,encoder layers,and the weights of the loss function.The experimental results demonstrate the significant contributions of data augmentation,hyperparameter tuning,and error correction models to the overall model performance.On the Our ATC Corpus dataset,the proposed model achieves a Character Error Rate(CER)of 3.44%,representing a 3.64%improvement compared to the baseline model.Moreover,the effectiveness of the proposed model is validated on two publicly available datasets.On the AISHELL-1 dataset,the CCAT model achieves a CER of 3.42%,showcasing a 1.23%improvement over the baseline model.Similarly,on the LibriSpeech dataset,the CCAT model achieves a Word Error Rate(WER)of 5.27%,demonstrating a performance improvement of 7.67%compared to the baseline model.Additionally,this paper proposes an evaluation criterion for assessing the robustness of ATC speech recognition systems.In robustness evaluation experiments based on this criterion,the proposed model demonstrates a performance improvement of 22%compared to the baseline model.

China’s Monetary Policy Impacts on Money and Stock Markets

This study investigated the impact of China’s monetary policy on both the money market and stock markets,assuming that non-policy variables would not respond contemporaneously to changes in policy variables.Monetary policy adjustments are swiftly observed in money markets and gradually extend to the stock market.The study examined the effects of monetary policy shocks using three primary instruments:interest rate policy,reserve requirement ratio,and open market operations.Monthly data from 2007 to 2013 were analyzed using vector error correction(VEC)models.The findings suggest a likely presence of long-lasting and stable relationships among monetary policy,the money market,and stock markets.This research holds practical implications for Chinese policymakers,particularly in managing the challenges associated with fluctuation risks linked to high foreign exchange reserves,aiming to achieve autonomy in monetary policy and formulate effective monetary strategies to stimulate economic growth.

Water level updating model for flow calculation of river networks

Complex water movement and insufficient observation stations are the unfavorable factors in improving the accuracy of flow calculation of river networks. A water level updating model for river networks was set up based on a three-step method at key nodes, and model correction values were collected from gauge stations. To improve the accuracy of water level and discharge forecasts for the entire network, the discrete coefficients of the Saint-Venant equations for river sections were regarded as the media carrying the correction values from observation locations to other cross-sections of the river network system. To examine the applicability, the updating model was applied to flow calculation of an ideal river network and the Chengtong section of the Yangtze River. Comparison of the forecast results with the observed data demonstrates that this updating model can improve the forecast accuracy in both ideal and real river networks.

Cointegration analysis with structural changes between consumption and economic growth in China

In order to investigate the existence of a stable long-run equilibrium relationship between economic growth and consumption in China, the relationship between the gross domestic product （GDP） and consumption in China was investigated by the cointegration analysis method. Using the Engle-Granger （EG） test and considering the possibility of structural changes, the impact of external economic shocks on the long-run equilibrium relationship between economic growth and consumption in China was analyzed. Analysis results show that without considering structural changes, the EG test cannot detect cointegration in the series subjected to structural changes; in considering structural changes, cointegration is successfully detected by specifying the dummy variable. In addition, the error correction models were constructed in different periods. This study verifies the existence of a long-run equilibrium relationship between economic growth and consumption in China, and this relationship has significantly changed in 1989 and 1997, respectively.

GRA BASED ANALYSIS ON FACTORS INFLUENCING CO_2 EMISSIONS IN CHINA

How to achieve the objective of reducing CO2 emissions has been an academic focus in China recently. The factors influencing CO2 emissions are the vital issue to accomplish the arduous target. Firstly, three influential factors, the energy consumption, the proportion of tertiary industry in gross domestic product （GDP）, and the degree of dependence on foreign trade, are carefully selected, since all of them have closer grey relation with China＇s COz emissions compared with others when the grey relational analysis （GRA） method is applied. The study highlights co-integration relation of these four variables using the co-integration analysis method. And then a long-term co-integration equation and a short-term error correction model of China＇s CO2 emissions are devel- oped. Finally, the comparison is exerted between the forecast value and the actual value of China＇s CO2 emissions based on error correction model. The results and the relevant statistics tests show that the pro- posed model has better explanation capability and credibility.

Analysis of services trade and employment in China by co-integration and causality

This article describes a study by co-integration test and Granger causality test on the relationships between China's services trades and employment using the data of services trade from the WTO website and the employment data from China Statistic Yearbook for the years from 1982 to 2003. Co-integration test showed that 1% increase in export value and import value of services created respectively 0.205% and 0.068 7% more job opportunities in the service sector. Both export and import of services impacted positively on employment in service industry, and export did more than import. However, in the short run, the impacts of services export and import on employment in service industry were both very small, though positive; and the impacts of employment in service industry on both export and import of services were very big, but not stable. Granger causality test indicated that employment in service industry was a Granger cause of services export. The findings highlight the importance of facilitating services import and reducing import barriers, and suggest that the competitiveness of China's labor- intensive services trade can be exploited to boost services export and help employment in service sector, and that the structure of services trade should be optimized by shifting from labor-intensive to knowledge-and technology-intensive services thus to enhance China's competitiveness of services export.

Assessing the spillover effects of U.S.monetary policy normalization on Nigeria sovereign bond yield

This study examines the spillover effects of U.S.monetary policy normalization on Nigeria 10-Year Treasury bond yield between 2011 and 2017,using the vector error correction model approach.Our results reveal that domestic factors,such as exchange rate and inflation,rather than the U.S.10-Year sovereign bond yield,are the key drivers of Nigeria 10-Year bond yield.Additionally,the spillover effect from the U.S.monetary policy was amplified by oil price shocks and changes in Nigeria’s monetary policy rates.Our counterfactual analysis confirms the findings.

The impact of bank lending on Palestine economic growth:an econometric analysis of time series data

Banking is an essential sector of Palestine’s economy.More credits provided by banks are considered to have a positive impact on economic growth so that the overall objective of this study is to examine the impact of bank lending on economic growth in Palestine.The study employs the Augmented Dickey-Fuller to test for stationarity in the time series,The Johansen co-integration,Vector Autoregressive Model and Vector Error Correction Model are employed to identify the long-run and short-run dynamics among the variables,and Granger causality test in order to determine the direction of causality.The study finds that a long run relationship exists among the variables and insignificant short run relationship.Also,the study findings show that there is unidirectional causality and runs from GDP to bank lending.The insignificant contribution of bank lending to GDP is attributed to the fact that banks are not highly interested in lending to the production sector of the economy due to the high level of risk.However,the primary empirical evidence reveals that bank lending doesn’t cause economic growth,but economic growth causes bank lending.

Co-integration-based analysis of energy assurance for steady economic growth in China

By applying co-integration analysis,the Granger causality test and an error correction model,the dependency between the energy consumption and the gross domestic product of China was examined.In a further step an analysis was done to establish a correlation between the economic growth of different industries and China's energy consumption.An evidence-based study showed that a co-integration relationship exists between the gross energy consumption and the GDP of China and that the two variables possess bi-directional causality.The energy consumption for the secondary industry has a markedly stimulative effect to the economic growth.This paper also uses an error correction model(ECM)to explain the short-term behavior of energy demands.

The Connection of Vegetation with Tourism Development and Economic Growth： A Case Study for Aruba

Vegetation is an important ecosystem on earth. It influences the earth system in many ways. Any influences on this fragile variable should be investigated, especially in a changing climate. Humans can have a positive or a negative influence on plants. This paper investigates the possible impact of tourism development and economic growth on vegetation health using cointegration and causality for Aruba. The proposed framework contributes to a better understanding on the use of remote sensing of vegetation response to tourism development and economic growth. Thereby, provide opportunities for improving the overall strategy for achieving sustainable development on a small island state. The calculations showed that there were relationships between the tourism demand and economic growth on the vegetation health on Aruba for the western part of the island. On the other hand, for the central part of the island, no relationships were found.

Impact of Sub-Economic on Money Supply in Nigeria: An Autoregressive Distribution Lag (ARDL) Approach

The escalation in dollar rates and the price instability in the Nigerian economy went through some significant structural and institutional changes such as the liberalization of the external trade, the elimination of price and interest rate controls, and the adoption of a managed float exchange rate system as well as the changes in monetary policy including innovations in the banking sector. Hence, the study examines the impact of financial development on money demand in Nigeria by means of ARDL approach. It examined the quarterly returns of M2, exchange rate (EXR), inflation rate (IFR), currency in credits to private sector (CPS) and circulation (CIC). The data span from 1991 to 2018. The study utilizes regression model techniques where the regression model’s residual is tested for Cointegration using Engle-Granger residual approach, the significances of the variable’s co-movement are checked by pairwise Granger Causality tests and ARDL and VECM are estimated in order to account for the short run and long run relationship among the variables. From the empirical results, Engle-Granger residuals and pairwise Granger Causality tests confirm cointegration among variables. The ARDL and VECM confirm the long run relation between money demand (M2) and financial development variables: CPS and CIC. ARDL models (short run relationship) are estimated for exchange rate and inflation rate. Long run (VECM) analysis has confirmed significance of financial development variables (CPS and CIC) with positive sign;implies that money demand function is stable in long run. The VECM granger causality results reveal that bidirectional causality exists between currency in circulation and money demand in both short and long run. Unidirectional causal relationship exists between credits to private sector and money demand in both short and long run. Hence, government should pay more attention on financial development and ensure a coordination of both fiscal and monetary policy.

Financial Development, Trade Openness, and Economic Growth in Zambia

This study investigates the causal relationship among financial development, trade openness, and economic growth in Zambia from 1965 to 2011. Two measures of financial development were used： broad money and domestic credit to the private sector, each as a ratio of gross domestic product （GDP）. In this regard, two models were developed for each indicator. The Augmented Dickey-Fuller （ADF） and Phillips-Perron （PP） tests were used to determine stationarity of all the variables. Furthermore, Johansen test was employed to ascertain possible cointegration among variables. The vector error correction model （VECM） was employed to examine the short-run and long-run dynamics among the variables in each model. The results indicate that the relationship among financial development, trade openness, and economic growth is sensitive to the financial development indicator chosen.

Predicting Bank Interests When Monetary Rates Are Close to Zero

Monetary policies, either actual or perceived, cause changes in monetary interest rates. These changes impact the economy through financial institutions, which react to changes in the monetary rates with changes in their administered rates, on both deposits and lendings. The dynamics of administered bank interest rates in response to changes in money market rates is essential to examine the impact of monetary policies on the economy. Chong et al. (2006) proposed an error correction model to study such impact, using data previous to the recent financial crisis. In this paper we examine the validity of the model in the recent time period, characterized by very low monetary rates. The current state of close-to-zero monetary rates is of particular relevance, as it has never been studied before. Our main contribution is a novel, more parsimonious, model and a predictive performance assessment methodology, which allows comparing it with the error correction model.

Environmental regulation and trade pattern:a case of China

As a growing number of countries, including both developed and developing countries, have in recent yearstaken environmental regulation at different levels, a question of great concern has been raised: can the regulation alterthe existing trade volume and trade pattern, and ultimately drive pollution-intensive industries to countries with low-levelregulations or even those without regulations at all? Starting from the three different propositions concerning therelationship between environmental regulation and trade pattern, this paper applies cointegration analysis and errorcorrection model to empirically testing the relationship between environmental regulation and trade in China during theperiod of 1985-2005. Our empirical results indicate that in the short run the collection of pollution discharge fees bearsa positive impact on the export share of clean products of total exports. Thus, higher pollution discharge fees raise theratio of clean products exports to total exports. This further indicates that more stringent environmental regulationpromotes the exports of clean products. In the long run pollution discharge fees are positively correlated with the exportshare of clean products but negatively associated with their import share. Such correlations imply that environmentalregulation tends to facilitate the international specialization in line with comparative advantages.

IMPACT OF SUMMER WARMING ON DYNAMICS-STATISTICS-COMBINED METHOD TO PREDICT THE SUMMER TEMPERATURE IN CHINA

Based on NCEP/NCAR daily reanalysis data, climate trend rate and other methods are used to quantitatively analyze the change trend of China's summer observed temperature in 1983—2012. Moreover, a dynamics-statistics-combined seasonal forecast method with optimal multi-factor portfolio is applied to analyze the impact of this trend on summer temperature forecast. The results show that: in the three decades, the summer temperature shows a clear upward trend under the condition of global warming, especially over South China, East China, Northeast China and Xinjiang Region, and the trend rate of national average summer temperature was 0.27℃ per decade. However, it is found that the current business model forecast(Coupled Global Climate Model) of National Climate Centre is unable to forecast summer warming trends in China, so that the post-processing forecast effect of dynamics-statistics-combined method is relatively poor. In this study, observed temperatures are processed first by removing linear fitting trend, and then adding it after forecast to offset the deficiency of model forecast indirectly. After test, ACC average value in the latest decade was 0.44 through dynamics-statistics-combined independent sample return forecast. The temporal correlation(TCC) between forecast and observed temperature was significantly improved compared with direct forecast results in most regions, and effectively improved the skill of the dynamics-statistics-combined forecast method in seasonal temperature forecast.

Relationships of the Monetary Policy, Stock Market and Real Investment in China Based on Markov-Switching Model

This paper studies the relationships of the monetary policy, stock market and real investment in China based on Markov-Switching-Vector Error Correction Model. It shows that there is a cointegration relationship among the three ones. We disclose the riddle that the stock market is in recession, but the growth rate of economy is very high in recent years. We also find that Chinese economy operated stably most of the time during the past 8 years. But if the economy is difficult to continue its high growth, it is more likely to appear ＂hard landing＂ than ＂soft landing＂. The impulse response analysis indicates the asymmetry between the ＂too cold＂ economy regime and the ＂too hot＂ regime. And the economy will oscillate during the subsequent time when it is shocked under the ＂too hot＂ regime.

Interaction Among Construction Investment,Other Investment and GDP in China

With Granger causality method, this paper examines the causal dynamics among three economic fundamentals: construction investment, other investment and the gross domestic product (GDP). Short-run and long-run interactive effects among these three time series are analyzed from 1981 to 2001. The empirical results show that construction investment has a stronger short-run effect on economic growth than other investment, and economic growth has a long-term effect on both construction and other investments. These findings indicate that construction investment is an important factor influencing short-term economic growth fluctuations, with its growth stimulating economic growth and its slumps leading to downside fluctuations. At the same time, invest-ment growth cannot be sustained without the support of the national economy. These empirical results have im-portant implications for economic policy makers in China.

Electricity Consumption and Economic Growth in the Beijing-Tianjin-Hebei Agglomeration of China

Nowadays, increased attention is being paid to the causal relationship between electricity consumption and economic growth. This paper attempts to examine the causal relationship between electricity consumption and economic growth for China＇s Beijing-Tianjin-Hebei agglomeration, using annual data covering the period 1982- 2008. In this study, unit root tests, the Johansen co-integration test, and the Granger causality test are applied. The empirical results indicate that the two series （electricity consumption and economic growth） of the three locales （Beijing, Tianjin, and Hebei） are non-stationary. But first differences of the two series are stationary. The results of the Johansen co-integration test indicate that electricity consumption and economic growth are co-integrated in Hebei and Tianjin while this is not the case in Beijing. The Granger causality test implies that there is causality running from electricity consumption to economic growth in all of the three locales. Causality running from economic growth to electricity consumption is found in Hebei and Beijing while this is not the case in Tianjin. This means that an increase in electricity consumption directly affects economic growth and that economic growth also stimulates further electricity consumption in Hebei and Beijing. But in Tianjin, an increase in electricity consumption directly affects economic growth while economic growth cannot affect electricity consumption. These findings can provide useful information for local governments of the three locales to formulate sustainable energy and economic policies. The study is of great significance for circular economy and building a resource-conserving society.