Is There Hysteresis in Unemployment in OECD Countries？ Evidence From Panel Unit Root Test With Structural Breaks

This study tests the hysteresis hypothesis of unemployment in fifteen OECD countries by using panel unit root tests which allow for structural breaks. We apply annual unemployment rates covering 1985-2008 periods. We test whether unemployment rates are stationary by using second generation tests which allow cross section dependency among series and panel unit root test based on structural break advanced by Carrion-i-Silvestre, Barrio-Castro and Lopez-Bazo （2005）. We find series as a stationary process with structural breaks according to Carrion-i Silvestre et al. （2005） test, while we find series as unit root process with second generation panel unit root test. According to the Carrion-i Silvestre et al. （2005） test, we find the evidence of absence of hysteresis in analyzed countries. As a result, temporary shocks have temporary effects on unemployment instead of permanent effect. Structural factors can affect the natural rate of unemployment and, therefore, unemployment would be stationary around a process that is subject to structural breaks. So, there still exists a unique natural rate of unemployment to which the economy eventually will converge.

Characterizing the Urban Temperature Trend Using Seasonal Unit Root Analysis:Hong Kong from 1970 to 2015

This paper explores urban temperature in Hong Kong using long-term time series. In particular, the characterization of the urban temperature trend was investigated using the seasonal unit root analysis of monthly mean air temperature data over the period January 1970 to December 2013. The seasonal unit root test makes it possible to determine the stochastic trend of monthly temperatures using an autoregressive model. The test results showed that mean air temperature has increased by 0.169~ C （10 yr） - 1 over the past four decades. The model of monthly temperature obtained from the seasonal unit root analysis was able to explain 95.9% of the variance in the measured monthly data -- much higher than the variance explained by the ordinary least-squares model using annual mean air temperature data and other studies alike. The model accurately predicted monthly mean air temperatures between January 2014 and December 2015 with a root-mean-square percentage error of 4.2%. The correlation between the predicted and the measured monthly mean air temperatures was 0.989. By analyzing the monthly air temperatures recorded at an urban site and a rural site, it was found that the urban heat island effect led to the urban site being on average 0.865~C warmer than the rural site over the past two decades. Besides, the results of correlation analysis showed that the increase in annual mean air temperature was significantly associated with the increase in population, gross domestic product, urban land use, and energy use, with the R2 values ranging from 0.37 to 0.43.

A Unit Root Test for an AR(1)Process with AR Errors by Using Random Weighted Bootstrap

A great deal of economic problems are related to detecting the stability of time series data,where the main interest is in the unit root test.In this paper,we consider the unit root testing problem with errors being long-memory processes with the LARCH structure.A new test statistic is developed by using the random weighted bootstrap method.It turns out that the proposed statistic has a chisquared distribution asymptotically regardless of the process being stationary or nonst at ionary,and with or without an intercept term.The simulation results show that the statistic has a desired finite sample performance in terms of both size and power.A real data application is also given relying on the inflation rate data of 17 countries.

The Classification to Stationary Process of Tidal Motion Observed at the Time of Kuroshio’s Meandering

The tide level displays information about the state of the sea current and the tidal motion. The tide level of the southern coast of Japan Island is affected strongly by Kuroshio Current flowing in the western part of North Pacific Ocean. When Kuroshio takes the straight path and flow along the Japan Islands, the tide level increases, and it is calculated from two tide level data observed at Kushimoto and Uragami in the southern part of Kii Peninsula. In contrast, the tide level decreases at the time when Kuroshio leaves from the Japan Islands. In this paper, the hourly tidal data are analyzed using the Autocorrelation Function (ACF) and the Mutual Information (MI) and the phase trajectories at first. We classify the results into 5 types of tidal motion. Each categorized type is investigated and characterized precisely using the mean tide level and the unit root test (ADF test) next. The frequency of the type having unstable tidal motion increases when the Kuroshio Current is non-meandering or in a transition state or the tide level is high, and the type shows a non-stationary process. On the other hand, when the Kuroshio Current meanders, the tidal motion tends to take a periodical and stable state and the motion is a stationary process. Though it is not frequent, we also discover a type of stationary and irregular tidal motion.

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.

The ASEAN experience of the purchasing power parity theory

We used panel data analysis to evaluate the relative purchasing power parity(PPP)hypothesis of the ten ASEAN member countries between 1973 and 2015.We incorporated the cross-sectionally augmented panel unit root test as proposed by Pesaran(J Appl Econ 22:265-312,2007).For panel cointegration analysis,we employed the four error-correction-based Westerlund(Oxf Bull Econ Stat 69:709-748,2007)panel cointegration tests.The Westerlund(Oxf Bull Econ Stat 69:709-748,2007)tests are general enough to permit a large degree of heterogeneity,both in the long-run cointegrating relationship and in the short-run dynamics,and dependence within as well as across the cross-sectional units.To check the robustness of the results,we further estimated the cointegration test excluding Indonesia and Brunei.The findings support our initial results.Further,all the results overwhelmingly support the relative PPP hypothesis.Consequently,the monetary authority would be able to implement a self-regulating monetary policy.It would also be able to control the exchange rates.

Impact of Inflation, Dollar Exchange Rate and Interest Rate on Red Meat Production in Turkey： Vector Autoregressive （VAR） Analysis

In this study, impact of inflation （WPI--Wholesale Price Index）, exchange rate, and interest rate on the production of red meat in Turkey was examined using the vector autoregressive （VAR） model. The model consisting of variables of dollar exchange rate, inflation rate, interest rate, beef, buffalo meat, mutton, and goat meat production amounts has been estimated for the period from 1981 to 2014. It has been detected that there is a tie among the dollar exchange rate, inflation rate, interest rate, and the amount of red meat production in Turkey. In order to determine the direction of this relation, Granger causality test was conducted. A one-way causal relation has been observed between： the goat meat production and dollar exchange rate; the buffalo meat production and the mutton production; and the beef production and the mutton production. To interpret VAR model, the impulse response function and variance decomposition analysis was used. As a result of variance decomposition, it has been detected that explanatory power of changes in the variance of dollar exchange rate, inflation rate, and interest rate in goat meat production amount is more than explanatory power of changes in the variances of mutton, beef, and buffalo meat variables.

Problems Existed in Applications of Cointegration Theory in China

Although the Cointegration Theory was founded by the C.W.J Granger and other economists in the 1980s, it was not widely used in China until C.W.J Granger was awarded with Nobel Prize in 2003. Since then, a lot of economic papers introducing or applying Cointegration Theory have emerged, but the phenomenon of misuse of this theory possibly arose at the same time. Based on some of these papers obtained from web site （www.cnki.net）, this paper explores the applications of Cointegration Theory in China and draws some initial conclusions. Most of these applications are reasonable, but some of them are a bit blindfold or even contradictory in conclusions, which indicates that the overall application quality has a large room to get improved and should be paid more attention by academe.

The weak form market efficiency investigation of American, European and Asian stock markets

This paper investigates the empirical validity of the Weak Form Efficient Market Hypothesis for American, European and Asian stock markets. Random Walk Hypothesis is used to prove weak form efficiency in American, European and Asian stock indices. ADF and PP Unit Root Tests have been used to test unit root in time series of daily data of American, European and Asian stock indices. Results show that sample of stock markets are weak-form efficient in terms of the Random Walk Hypothesis.

Relationship between the price of green tea and black tea of the world’s major tea countries

Black tea and green tea are the most important tea in the world.In this paper we analyze the relationship of the world green price and black tea price.The results show that:in the world tea markets,the world black tea price and the world green tea price have no co-integration,independent of the curve segmentation.In the major green tea countries,there are co-integration relationships between China and Japan,China and Brazil,Japan and Brazil,while Vietnam has a first-order stationary sequence.In the major black tea countries,Sri Lanka and India have no co-integration,Sri Lanka and Indonesia no co-integration,India and Indonesia no co-integration,Sri Lanka and Kenya have co-integration,India and Kenya have co-integration,Kenya and Indonesia have co-integration.

Research on Prediction of the Scale of OTC Drug Market in China Based on Quantitative Analysis

Objective To analyze the scale of domestic OTC drug market and its influencing factors,so as to predict its future market and provide a scientific basis for pharmaceutical enterprises to grasp the opportunities in the market.Methods The scale of OTC drug market from 1999 to 2018 in China and its influencing factors were analyzed by unit root test,Granger causality test and co-integration test.Results and Conclusion From the perspective of the global pharmaceutical market,OTC drug market has broad prospects and great development potential.Since the influence of GDP and the number of elderly populations on the scale of OTC drug market is positive,the predicted growth rate of OTC market in the next three years is 5.82%,5.86%and 5.90%,respectively.

THE LIMIT THEOREM FOR DEPENDENT RANDOM VARIABLES WITH APPLICATIONS TO AUTOREGRESSION MODELS

This paper studies the autoregression models of order one, in a general time series setting that allows for weakly dependent innovations. Let {Xt} be a linear process defined by Xt =∑k=0^∞ψ kεt-k, where {ψk, k ≥ 0} is a sequence of real numbers and {εk, k = 0, ±1, ±2,...} is a sequence of random variables. Two results are proved in this paper. In the first result, assuming that {εk, k ≥ 1} is a sequence of asymptotically linear negative quadrant dependent （ALNQD） random variables, the authors find the limiting distributions of the least squares estimator and the associated regression t statistic. It is interesting that the limiting distributions are similar to the one found in earlier work under the assumption of i.i.d, innovations. In the second result the authors prove that the least squares estimator is not a strong consistency estimator of the autoregressive parameter a when {εk, k ≥ 1} is a sequence of negatively associated （NA） random variables, and ψ0 = 1, ψk = 0, k ≥ 1.