scholarly journals Structural Breaks and Unit Root: Evidence from Pakistani Macroeconomic Time Series

2006 ◽  
Author(s):  
Muhammad Waheed ◽  
Tasneem Alam ◽  
Saghir Pervaiz Ghauri
Keyword(s):  
Time Series ◽  
Unit Root ◽  
Structural Breaks ◽  
Macroeconomic Time Series

scholarly journals UNDERSTANDING INDONESIA’S MACROECONOMIC DATA: WHAT DO WE KNOW AND WHAT ARE THE IMPLICATIONS?

2018 ◽  
Vol 21 (2) ◽  
pp. 229-264 ◽  
Author(s):  
Susan Sunila Sharma
Keyword(s):  
Time Series ◽  
Unit Root ◽  
Structural Breaks ◽  
Time Series Data ◽  
Unit Roots ◽  
Series Data ◽  
Econometric Modelling ◽  
Shock Response ◽  
Macroeconomic Time Series ◽  
Root Properties

Unit root properties of macroeconomic data are important for both econometric modelling specifications and policy making. The form of variables (whether they are a unit root process) helps determine the correct econometric modelling. Equally, the form of variables helps explain how they react to shocks (both internal and external). Macroeconomic time-series data are often at the forefront of shock analysis and econometric modelling. There is a growing emphasis on research on Indonesia using time-series data; yet, there is limited understanding of data characteristics and shock response of these data. Using an extensive dataset comprising 33 macroeconomic time-series variables, we provide an informative empirical analysis of unit root properties of data. We find that regardless of data frequencies the empirical evidence of unit roots is mixed, some series respond quickly to shocks others do take time, and almost every macroeconomic data suffers from structural breaks. We draw implications of these findings.

scholarly journals Structural Breaks and Explosive Behavior in the Long-Run: The Case of Australian Real House Prices, 1870–2020

2021 ◽  
Vol 15 (1) ◽  
pp. 72-84
Author(s):  
Vicente Esteve ◽  
Maria A. Prats
Keyword(s):  
Time Series ◽  
Unit Root ◽  
Structural Breaks ◽  
House Prices ◽  
Unit Root Tests ◽  
Annual Data ◽  
Bubble Behavior ◽  
Long Period ◽  
Long Run ◽  
Long Time

Abstract In this article, we use tests of explosive behavior in real house prices with annual data for the case of Australia for the period 1870–2020. The main contribution of this paper is the use of very long time series. It is important to use longer span data because it offers more powerful econometric results. To detect episodes of potential explosive behavior in house prices over this long period, we use the recursive unit root tests for explosiveness proposed by Phillips et al. (2011), (2015a,b). According to the results, there is a clear speculative bubble behavior in real house prices between 1997 and 2020, speculative process that has not yet been adjusted.

The nature of Austrian macroeconomic time series unit root tests

Empirica ◽  
1990 ◽  
Vol 17 (2) ◽  
pp. 131-154
Author(s):  
Thomas Url ◽  
Gert Wehinger
Keyword(s):  
Time Series ◽  
Unit Root ◽  
Unit Root Tests ◽  
Macroeconomic Time Series

scholarly journals STUDY OF TESTS FOR TREND IN TIME SERIES

2021 ◽  
Vol 39 (2) ◽  
pp. 311-333
Author(s):  
Denise de Assis PAIVA ◽  
Thelma SÁFADI
Keyword(s):  
Time Series ◽  
Unit Root ◽  
Structural Breaks ◽  
Consumer Price Index ◽  
Unit Root Tests ◽  
Metropolitan Region ◽  
Maximum Temperature ◽  
Pettitt Test ◽  
Using Data ◽  
Time Series Methodology

The time series methodology is an important tool when using data over time. The time series can be composed of the components trend (Tt), seasonality (St) and the random error (at). The aim of this study was to evaluate the tests used to analyze the trend component, which were: Pettitt, Run, Mann-Kendall, Cox-Stuart and the unit root tests (Dickey-Fuller, Dickey-Fuller Augmented and Zivot and Andrews), given that there is a discrepancy between the test results found in the literature. The four series analyzed were the maximum temperature in the Lavras city, MG, Brazil, the unemployment rate in the Metropolitan Region of S~ao Paulo (RMSP), the Broad Consumer Price Index (IPCA) and the nominal Gross Domestic Product (GDP) of Brazil. It was found that the unit root tests showed similar results in relation to the presence of the stochastic trend for all series. Furthermore, the turning point of the Pettitt test diverged from all the structural breaks found through the Zivot and Andrews test, except for the GDP series. Therefore, it was found that the trend tests diverged, obtaining similar results only in relation to the unemployment series.

Measuring the effect of land degradation and environmental changes on agricultural production in Somalia with two structural breaks

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Abdinur Ali Mohamed ◽  
Ahmed Ibrahim Nageye
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Land Degradation ◽  
Unit Root ◽  
Agricultural Production ◽  
Crop Production ◽  
Structural Breaks ◽  
Environmental Changes ◽  
Content Type ◽  
Long Run

PurposeThe purpose of this study is to measure the effect of land degradation and the environmental changes on agricultural productivity in Somalia, as well as the other factors that affect crop production in Somalia.Design/methodology/approachCobb-Douglas production function assumes crop production as a dependent variable and land degradation, labor, capital, fertilizer and climate change as the explanatory variables. In this study time-series data (1962–2017) collected from the Food and Agriculture Organization and World Development Indicators were used. The unit root of the data was examined using Ng-Perron and the Lee-Strazicich methods to explore the unit root property of the breaks. Structural breaks are observed using the Chow test, and the long-run relationship between the variables is examined using Gregory and Hanssen's approach.FindingsThis study found that land degradation and climate change have a negative relationship with agriculture production in Somalia. Land degradation leads to the decline in agricultural production as the loss of one hectare of land due the depletion causes agriculture production of Somalia to fall by about five percent. Climate changes and warming of the environment lead to the reduction of agriculture production. One degree Celsius rise in the temperature leads to a three percent decline in agricultural production. Capital contributes immensely to agricultural production as one unit of additional capital raises production by seven percent. The contribution of labor to agricultural production is limited because of land contractionPractical implicationsLand degradation is a significant contributor to the decline of agricultural production. As land degradation continues to worsen, rural poverty increases, which in turn causes the rural migration and the social conflict. The government should develop land improvement programs such as increasing market orientation of the farmers, encourage private sector engagement in agribusiness and establish a regulatory framework of the land uses.Originality/valueThis study examines the structure of the time-series and specifies the break periods to determine when and where significant and sudden changes occurred within land degradation and agricultural production. The study employs advanced econometric methods, namely, Ng-Perron method and the Lee-Strazicich method to test the unit root property of the breaks. It also examines the long-run relationship between the variables using Gregory and Hanssen's approach.

Prices of short-stay accommodation: time series of a eurozone country

2019 ◽  
Vol 31 (12) ◽  
pp. 4500-4519 ◽  
Author(s):  
Sergej Gričar ◽  
Štefan Bojnec
Keyword(s):  
Time Series ◽  
Unit Root ◽  
Structural Breaks ◽  
Short Stay ◽  
Content Type ◽  
Vector Autoregressive ◽  
Long Run ◽  
Time Series Modelling ◽  
Overnight Stays ◽  
Practical Implications

Purpose This paper aims to provide a reliable statistical model for time-series prices of short-stay accommodation and overnight stays in a eurozone country. Design/methodology/approach Exploiting the unit root feature, the cointegrated vector autoregressive model solves the problem of misspecification. Subsequently, variables are modelled for a long-run equilibrium with included deterministic variables. Findings The empirical results confirmed that overnight stays for foreign tourists were positively associated with the prices of short-stay accommodation. Research limitations/implications The major limitation lies in the data vector and its time horizon; its extension could provide a more specific view. Practical implications Findings can assist practitioners and hotel executives by providing the information and rationale for adopting seasonal volatility pricing. Structural breaks in price time-series have practical implications for setting seasonal-pricing schemes. Tourists could benefit either from greater price stability or from differentiated seasonal prices, which are important in the promotion of the price attractiveness of the tourist destination. Originality/value The originality of the paper lies in the applied unit root econometrics for tourism price time-series modelling and the prediction of short-stay accommodation prices.

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