scholarly journals ARDL as an Elixir Approach to Cure for Spurious Regression in Nonstationary Time Series

Mathematics ◽  
2021 ◽  
Vol 9 (22) ◽  
pp. 2839
Author(s):  
Ghulam Ghouse ◽  
Saud Ahmad Khan ◽  
Atiq Ur Rehman ◽  
Muhammad Ishaq Bhatti
Keyword(s):  
Time Series ◽  
Unit Root ◽  
Time Series Data ◽  
Cointegration Analysis ◽  
Series Data ◽  
Testing Procedures ◽  
Spurious Regression ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
Unit Root Testing

In conventional Econometrics, the unit root and cointegration analysis are the only ways to circumvent the spurious regression which may arise from missing variable (lag values) rather than the nonstationarity process in time series data. We propose the Ghouse equation solution of autoregressive distributed lag mechanism which does not require additional work in unit root testing and bound testing. This advantage makes the proposed methodology more efficient compared to the existing cointegration procedures. The earlier tests weaken their position in comparison to it, as they had numerous linked testing procedures which further increase the size of the test and/or reduce the test power. The simplification of the Ghouse equation does not attain any such type of error, which makes it a more powerful test as compared to widely cited exiting testing methods in econometrics and statistics literature.

scholarly journals Is Islamic Bank More Stable Than Conventional Bank? Evidence From Islamic Rural Banks in Indonesia

2021 ◽  
Vol 12 (2) ◽  
pp. 294
Author(s):  
Agus Widarjono ◽  
M. B. Hendrie Anto ◽  
Faaza Fakhrunnas
Keyword(s):  
Time Series ◽  
Financial Stability ◽  
Time Series Data ◽  
Series Data ◽  
Z Score ◽  
Profit Rate ◽  
Return On Assets ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
Better Than

This study investigates whether Islamic rural banks perform better than conventional rural banks as their competitor in Indonesia. To measure Islamic rural banks' financial performance, we apply financial stability using Z-score and profitability using the return on assets. We use monthly time series data from January 2009 to December 2018. The dynamic regression of the Autoregressive Distributed Lag (ARDL) model is then employed. The results report that the Z-Score of Islamic rural banks is higher than the Z-Score of conventional rural banks. This finding shows that Islamic rural banks are less risky than conventional rural banks. However, the Islamic rural banks' financial stability is very vulnerable to changes in equity, output, and inflation than conventional rural banks. Although the Islamic rural banks' profit rate is lower compared to conventional rural banks, it is considered more stable. The profit of Islamic rural banks is affected by size, equity, domestic output, and inflation.

scholarly journals Tinjauan terhadap Metode Ekonometrika Lanjutan

2003 ◽  
Vol 4 (1) ◽  
pp. 59-74
Author(s):  
Telisa Aulia Falianty
Keyword(s):  
Genetic Algorithm ◽  
Time Series ◽  
Panel Data ◽  
Unit Root ◽  
Time Series Data ◽  
Random Effect ◽  
Unit Root Test ◽  
Cointegration Analysis ◽  
Series Data ◽  
Theory Of Evolution

Econometric models have been played an increasingly important role in empirical analysis in economics. This paper provides an overview on some advanced econometric methods that increasingly used in empirical studies.A panel data combines features of both time series and cross section data. Because of increasing availability of panel data in economic sciences, panel data regression models are being increasingly used by researcher. Related to panel data model, there are some methods that will be discussed here such as fixed effect and random effect. A new approach to panel data that developed by Im, Shin, and Pesaran (2002) for testing unit root in heterogenous panel is included in this overview.When we work with time series data, there are many problems that we must handle, most of them are unit root test, cointegration among non stationary variables, and autoregressive conditional heteroscedasticity. Provided these problems, author also review about ADF and Philips-Perron test. An approch to cointegration analysis developed by Pesaran (1999), ARCH and GARCH model are also interesting to be discussed here.Bayesian econometric, that less known than classical econometric, is includcd in this overview. The genctic algorithm, a relatively new method in econometric, has bcen increasingly employed the behavior of economic agents in macroeconomic models. The genetic algorithm is based on thc process of Darwin’s Theory of Evolution. By starting with a set of potential solutions and changing them during several iterations, the Genetic Algorithm hopes to converge on the most ‘fit’ solutions.

Detecting true relationships in time series data with different orders of integration

2021 ◽  
pp. 1-13
Author(s):  
Peter K. Enns ◽  
Carolina Moehlecke ◽  
Christopher Wlezien
Keyword(s):  
Time Series ◽  
Type I Error ◽  
Time Series Data ◽  
Proper Time ◽  
Series Data ◽  
Type I ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
Left And Right ◽  
True Relationship

Abstract It is fairly well-known that proper time series analysis requires that estimated equations be balanced. Numerous scholars mistake this to mean that one cannot mix orders of integration. Previous studies have clarified the distinction between equation balance and having different orders of integration, and shown that mixing orders of integration does not increase the risk of type I error when using the general error correction/autoregressive distributed lag (GECM/ADL) models, that is, so long as equations are balanced (and other modeling assumptions are met). This paper builds on that research to assess the consequences for type II error when employing those models. Specifically, we consider cases where a true relationship exists, the left- and right-hand sides of the equation mix orders of integration, and the equation still is balanced. Using the asymptotic case, we find that the different orders of integration do not preclude identification of the true relationship using the GECM/ADL. We then highlight that estimation is trickier in practice, over finite time, as data sometimes do not reveal the underlying process. But, simulations show that even in these cases, researchers will typically draw accurate inferences as long as they select their models based on the observed characteristics of the data and test to be sure that standard model assumptions are met. We conclude by considering the implications for researchers analyzing or conducting simulations with time series data.

scholarly journals Financial Development, Remittances Inflows and Economic Growth in Nigeria: A Time Series Analysis

2020 ◽  
pp. 37-43
Author(s):  
Eric Olabode Olabisi ◽  
Sunday Oseiweh Ogbeide
Keyword(s):  
Economic Growth ◽  
Time Series ◽  
Financial Development ◽  
Time Series Data ◽  
Financial Institution ◽  
Series Data ◽  
Significant Variable ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
The Government

This study examines whether financial development promotes remittances inflows and Nigerian economic growth. Using a time-series data for a period of 1985-2017, the Autoregressive Distributed Lag (ARDL) technique was employed. The results suggest that financial development in Nigeria exerted no significant impact on economic growth. It is an indication that financial development is not a significant variable for promoting remittances inflows into Nigeria. However, the study concludes that remittances inflows are a substitute for promoting individual’s financial business opportunities and economic growth. The study therefore recommends that the government should strengthen the Nigeria financial institution, and also institute a financial reform initiative that can enhance financial security as well as ease of accessing remittances inflows.

Macro-Economic Disequilibrium and Educational Development in Nigeria between 1980-2017

2019 ◽  
Vol 10 (08) ◽  
pp. 20592-21600
Author(s):  
Gbadebo Salako ◽  
Adejumo Musibau Ojo ◽  
Jaji Ayobami Francis
Keyword(s):  
Time Series Data ◽  
Educational Development ◽  
Negative Relationship ◽  
Series Data ◽  
Explanatory Variables ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
Long Run ◽  
Stationarity Test ◽  
Level I

This study empirically investigates the effects of macroeconomic disequilibrium on educational development in Nigeria. The study employed time series data between 1980 and 2017. Autoregressive Distributed Lag method of estimation was employed. The result revealed that the variables stationarity test were mixed between the first difference I(I) and level I(0). The cointegration result shows that there exist long run relationship between the variables. The result revealed that Balance of payment, Poverty, Debt rate inflation and unemployment exhibited negative relationship with educational development. The estimation result showed that all explanatory variables account for 88% variation of educational development in Nigeria. It is therefore recommended that government should fast track policies that can stabilize inflation and exchange rate in the country. Also, Policies must be formulated to reduce poverty and unemployment.

scholarly journals Financial Deepening And Financial Performance Of Deposit Money Banks In Nigeria

2019 ◽  
Vol 6 (11) ◽  
pp. 179-191
Author(s):  
Mulkat Ajibola Yusuff ◽  
Fatimah Olabisi Olaniran-Akinyele
Keyword(s):  
Private Sector ◽  
Financial Performance ◽  
Time Series Data ◽  
Negative Influence ◽  
Series Data ◽  
Financial Deepening ◽  
Return On Equity ◽  
Market Capitalization ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag

This study examines the effect of financial deepening on financial performance of Nigerian Deposit Money Banks using time-series data spanning 1990Q1-2017Q4. The financial performance is expressed by return on assets (ROA) and return on equity (ROE) with total bank liability, private sector credit and market capitalization as measure of financial deepening. The technique of analysis deployed is autoregressive distributed lag (ARDL) to co integration. The findings show that the effect of total bank liability is positive and significant. Market capitalization and private sector credit on the other hand exert negative and significant effect. The study concludes that financial deepening affect financial performance of Deposit Money Banks in Nigeria. It then recommends effective loan recovery strategy to mitigate the negative influence of private sector credit due to non-performing loans.

Factors Determining Gold Prices in Malaysia

2019 ◽  
Vol 1 (2) ◽  
pp. 75-82
Author(s):  
Anis Mat Dalam ◽  
Noorhaslinda Kulub Abd Rashid ◽  
Jaharudin Padli
Keyword(s):  
Crude Oil ◽  
Time Series Data ◽  
Oil Prices ◽  
Series Data ◽  
Distributed Lag ◽  
Autoregressive Distributed Lag ◽  
Crude Oil Prices ◽  
Inflation Rates ◽  
Ardl Approach ◽  
Gold Reserve

Gold is a valuable asset to a country because of its liquidity. Gold reserve can stabilize the currency in a country. The objective of this paper is to identify the factors contributing to the volatility of gold prices, such as Real Malaysia GDP, inflation rates, crude oil prices and exchange rates. The data was analysed using Autoregressive Distributed Lag (ARDL) approach with time series data, with 30-year coverage from 1987 to 2016. Findings showed that only Real Malaysia GDP and crude oil prices were significantly related to gold prices. As a conclusion, this study can be used as reference by other investors. The author suggests to other researchers to further improve upon this study by adding more variables or diversifying the variables that relate to volatility of gold prices.

scholarly journals Exploring OECD SDGs pilot city's 50-year time series data and its Environmental Kuznets Curves

2019 ◽  
Author(s):  
Quan-Hoang Vuong ◽  
Tung Manh Ho ◽  
NGUYỄN Minh Hoàng
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Series Data ◽  
Kuznets Curve ◽  
Infrastructure Development ◽  
Low Carbon ◽  
Industrial Firms ◽  
Distributed Lag ◽  
Size Growth ◽  
Paved Road

Can green growth policies help protect the environment while keeping the industry growing and infrastructure expanding? This study applies Auto-Regressive Distributed Lag (ARDL) method on the 50-years’ time series data, from 1967 to 2015, of Kitakyushu City, Japan, and found mixed evidence for Environmental Kuznets Curve (EKC) hypothesis. The analyses of NO2, Ox, falling dust particle, and SOx highlight a trilemma among the growth of industrial firms, infrastructure development, and reducing air-quality degradation. Nevertheless, for CO emission per capita, its logarithm has a general declining trend when plotted against both average firm size growth and paved road area expansion. This finding sheds light on the possibility of developing a regulatory framework that can harmonize a low-carbon society with industrial and infrastructure development.

scholarly journals Consumer Spending and Consumer Confidence in South Africa: Cointegration Analysis

2014 ◽  
Vol 6 (2) ◽  
pp. 95-104
Author(s):  
John Khumalo
Keyword(s):  
Economic Growth ◽  
South Africa ◽  
Unit Root ◽  
Time Series Data ◽  
Positive Impact ◽  
Cointegration Analysis ◽  
Consumer Confidence ◽  
Series Data ◽  
Consumer Spending ◽  
Long Run

The study uses the time series data covering the period 1980Q1 to 2012Q3 to test the existence of any possible long run relationship between consumer spending and consumer confidence in South Africa. The analysis is done using the Vector Auto-Regressive (VAR) model, with the unit root and the direction of causation also tested before any inference can be concluded on this relationship. The unit root tests using the DF-GLS as well as the Ng-Peron show that consumer spending, consumer confidence and economic growth are integrated of order zero ~I(0). Causality results on the other hand reveal that causation runs from consumer confidence to consumer spending and from economic growth to consumer spending in South Africa. The non-existence of unit root compels the establishment of the long-run relationship that leads us to performing VECM to establish short-run and long-run dynamics. Our results indicate that the positive effect of consumer confidence cannot be refuted in South Africa and that it exerts a significant and positive impact on consumer spending, hence aggregate spending.

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