scholarly journals Panel Cointegration Testing in the Presence of Linear Time Trends

2014 ◽  
Author(s):  
Uwe Hassler ◽  
Mehdi Hosseinkouchack
Keyword(s):  
Time Trends ◽  
Linear Time ◽  
Panel Cointegration ◽  
Cointegration Testing

scholarly journals Panel Cointegration Testing in the Presence of Linear Time Trends

Econometrics ◽  
2016 ◽  
Vol 4 (4) ◽  
pp. 45 ◽  
Author(s):  
Uwe Hassler ◽  
Mehdi Hosseinkouchack
Keyword(s):  
Time Trends ◽  
Linear Time ◽  
Panel Cointegration ◽  
Cointegration Testing

scholarly journals Estimating the Potential Output and Output Gap of Ghana

2019 ◽  
Vol 6 (3) ◽  
pp. 58
Author(s):  
Joseph Atta-Mensah ◽  
Sawuya Nakijoba
Keyword(s):  
Economic Activity ◽  
Time Trends ◽  
Linear Time ◽  
Output Gap ◽  
Annual Data ◽  
Conceptual Tool ◽  
Potential Output ◽  
Economic Information ◽  
Hp Filter ◽  
Output Gaps

This paper focuses on the estimation of the potential output of Ghana. Potential output or its derivative the output gap are not observable. However, “potential output” is a powerful conceptual tool that guides analysts and policymakers in gauging whether the current observed economic activity is sustainable and how much of it is greater than or less than potential. Based on Ghanaian GDP annual data from 1960 – 2017, the paper estimates potential output and output gaps using the following methodology: linear time trends, Hodrick-Prescott (HP) filter trends, multivariate HP filter trends, and a production function model. The results show that estimates of the potential output and output gaps are model-dependent as estimates vary from one methodology to the other. The paper recommends that policymakers should not mechanically choose a model to estimate output gap. For the avoidance of costly policy mistakes, the choice of the model should be complemented with sound judgement based on a set of pertinent economic information.

scholarly journals STATISTICAL PROCESSING OF THE METEOROLOGICAL DATA FOR CONCLUSION ON THE PRESENCE OF THE TIME TRENDS

Doklady BGUIR ◽  
2020 ◽  
pp. 96-103
Author(s):  
V. S. Mukha
Keyword(s):  
Regression Analysis ◽  
Time Dependence ◽  
Time Trends ◽  
Linear Time ◽  
Meteorological Data ◽  
Linear Connection ◽  
Regression Function ◽  
Atmospheric Temperature ◽  
Meteorological Station ◽  
Positive Trend

The technic of the processing of the meteorological data for conclusion on the presence of the time trends in the quantitative characteristics of the weather on the example of the analysis of the average yearly atmospheric temperature change at the meteorological station Minsk from 1989 is presented. The average yearly atmospheric temperature received from the measurements is approximated by the least square error method in the linear time dependence regression function. The linear time dependence regression function received in such a way has some positive growing (positive trend). The aim of this paper is to clarify the significance of this growth. For this aim, the usage of the regression analysis with its procedures of hypotheses testing is proposed. First of all, the performing of the demands presented to the regression analysis is checked: normality of the distribution of the disturbance and the homogeneity of the variance (dispersion) of the disturbance. The normality of the distribution of the disturbance was checked and confirmed by the Kolmogorov test. The homogeneity of the dispersion of the disturbance was checked and confirmed both by checking the hypotheses on the equality of the dispersions of two normal distributions and by the Smirnov test for checking the hypotheses on the equality of two distributions. For checking the significance of the positive trend of the yearly mean temperature, the hypotheses on the significance of the coefficients of the linear regression function by the Student t-statistics and the hypothesis on the linear connection presence by the analysis of variance were checked. As the result, the insignificance of the positive linear trend from 1998 to 2016 and from 1998 to 2017 and its significance from 1998 to 2018 and from 1998 to 2019 on the level of significance 0.05 for mean average yearly atmospheric temperature at the meteorological station Minsk was stated.

LEADER AGE AND NATIONAL CONDITION: A LONGITUDINAL ANALYSIS OF 25 EUROPEAN MONARCHS

1984 ◽  
Vol 12 (2) ◽  
pp. 111-114 ◽  
Author(s):  
Dean Keith Simonton
Keyword(s):  
Time Series ◽  
Correlation Analysis ◽  
Time Trends ◽  
Partial Correlation ◽  
Linear Time ◽  
Royal Family ◽  
Partial Correlation Analysis ◽  
Cross Sectional ◽  
The Relationship ◽  
Foreign Wars

In order to determine the relationship between age and achievement in the politico-military domain, the reigns of 25 long-tenured European absolute monarchs were - analyzed as cross-sectional time series of 238 5-year age periods. Both linear and curvilinear age functions were defined along with variables to control for individual differences, linear time trends, and other potential artifacts. A partial correlation analysis indicated that leader age tends to be negatively correlated with military success in foreign wars and with treaty negotiation, and positively correlated with civil instability at home, whether in the royal family or in the populace. Moreover, some indicators of military and diplomatic success are curvilinear inverted U-functions of leader age, the peak approximately occurring in the leader's 42nd year.

scholarly journals Panel cointegration testing in the presence of a time trend

2014 ◽  
Vol 76 ◽  
pp. 377-390 ◽  
Author(s):  
Deniz Dilan Karaman Örsal ◽  
Bernd Droge
Keyword(s):  
Time Trend ◽  
Panel Cointegration ◽  
Cointegration Testing

TIME TRENDS IN CROP YIELDS IN LONG-TERM TRIALS

2000 ◽  
Vol 36 (2) ◽  
pp. 165-179 ◽  
Author(s):  
M. J. JONES ◽  
M. SINGH
Keyword(s):  
Time Trends ◽  
Crop Yields ◽  
Linear Time ◽  
Cropping Systems ◽  
Complex Model ◽  
Seasonal Effects ◽  
Yield Data ◽  
Growth Environment ◽  
Over Time

Trends over time in annual crop yields potentially provide measures of the likely long-term sustainability of cropping systems. However, where large annual variability in the growth environment is responsible for most of the large year-to-year yield differences, appropriate analytical techniques must be developed to distinguish real long-term trends from the ‘background noise’. This paper presents models for the estimation of time trends in the yield data from crop rotation systems and discusses the results of applying these models to yield values from two types of long-term trial involving barley, each conducted at two sites in northern Syria.The models used were linear with respect to time (years) and allowed for seasonal effects by means of a quadratic relationship on total rainfall and a linear relationship on planting date. A more complex model might account for more of the variance, but restrictions were imposed by the limited number of degrees of freedom (number of years of data less one) and the choice of meaningful single-valued parameters of growth-season conditions. For many experimental treatments the model accounted for less of the total variance at the wetter site. This may be due to seasonal bufferring by soil moisture stored at depth from one year to the next, and future iterations of the analysis will try to allow for this. The appropriateness of the linear time function is also questioned, and alternative functions will be tested along with alternative structures for plot errors over time.

scholarly journals The Returns to a Large Community College Program: Evidence from Admissions Lotteries

2020 ◽  
Vol 12 (1) ◽  
pp. 226-253
Author(s):  
Michel Grosz
Keyword(s):  
Community College ◽  
Time Trends ◽  
Fixed Effects ◽  
Linear Time ◽  
Health Care Industry ◽  
Market Returns ◽  
Care Industry ◽  
Percentage Points ◽  
College Programs ◽  
Associate's Degree

This paper estimates the labor market returns to the associate’s degree in nursing (ADN), which is one of the most popular community college programs. I use student-level academic and earnings records across two decades for all community college students in California. I leverage random variation from admissions lotteries to produce causal estimates of the effect of the ADN on earnings and employment at a single large ADN program. Enrolling in the program increases earnings by 44 percent and the probability of working in the health care industry by 19 percentage points. These estimates are similar to ones in models that do not use the lottery variation but do control for individual fixed effects and individual-specific linear time trends, which I also estimate in a wider set of institutions where lottery estimates are not possible. In light of concerns about nursing shortages, I estimate that the economic benefit of expanding an ADN program by one seat far outweighs the costs. (JEL D44, I11, I23, I26, J24, J31)

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