Results 281 to 290 of about 97,715 (338)

Forecast GDP with Autoregressive Distributed Lag Model and Dynamic Factor Model

Proceedings of the 2021 1st International Conference on Control and Intelligent Robotics, 2021
Several methods of time series forecast, including an ADL model, a parameric DFM, and a nonparametric DFM using PCA, were used to forecast US GDP in 2019 using time series data of quarterly US macroeconomic variables from the FRED database. Results were compared with each other and with the true value of GDP in 2019 to compare the models' predictive ...
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Modeling Nonlinear Autoregressive Distributed Lag Models: A New Approach

Journal of Quantitative Economics, 2005
It is a common practice in econometrics that estimation is carried out in terms of the reduced form parameters and the structural form parameters are retrieved using the functional relationship between structural form parameters and the reduced form parameters. The reduced form of many useful economic models is a nonlinear distributed lag model (NLADL)
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Multiscaled Neural Autoregressive Distributed Lag: A New Empirical Mode Decomposition Model for Nonlinear Time Series Forecasting

International Journal of Neural Systems, 2020
Forecasting has always been the cornerstone of machine learning and statistics. Despite the great evolution of the time series theory, forecasters are still in the hunt for better models to make more accurate decisions.
Foued Saâdaoui, Othman Ben Messaoud
semanticscholar   +1 more source

Determinants of Inflation in Ethiopia: An Autoregressive Distributed Lag Model.

SSRN Electronic Journal, 2020
Price stability is one of the major goals of monetary policy and the key indicators of macroeconomic stability. Pursuing of price stability is primary to long-run growth and development; it should be the concern of every economy. This study examine the factors in determining inflation in Ethiopia, using the autoregressive distributed lag (ARDL) model ...
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Autoregressive Distributed Lag Model of COVID-19 Infected Cases and Deaths

Journal of Statistics Applications & Probability, 2021
The primary objectives of the present study are to investigate the short- and long-term cointegration relationships between the cumulative number of new cases of COVID-19 infections (X) and the cumulative numbers of deaths due to COVID-19 (Y), to investigate the long-run equilibrium relationship between these variables using an autoregressive ...
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Does financial development asymmetrically affect CO2 emissions in China? An application of the nonlinear autoregressive distributed lag (NARDL) model

Carbon Management, 2018
The current study looks at the causes of carbon dioxide (CO2) emissions by considering the implications of financial development in the presence of economic growth and use of energy in the case of China over the period 1980–2014.
Manzoor Ahmad, Zeeshan Khan, Zia Ur Rahman, Shehzad Khan   +3 more
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Impact of climate change on food security in India: an evidence from autoregressive distributed lag model

Environment, Development and Sustainability, 2023
Biswabhusan Bhuyan, R. Mohanty, Subhamitra Patra   +2 more
semanticscholar   +1 more source

Do green finance and green innovation foster environmental sustainability in China? Evidence from a quantile autoregressive-distributed lag model

Environment, Development and Sustainability, 2023
Rui Dong, Shengnan Wang, M. A. Baloch
semanticscholar   +1 more source

Palm oil price forecasting model: An autoregressive distributed lag (ARDL) approach

AIP Conference Proceedings, 2017
Palm oil price fluctuated without any clear trend or cyclical pattern in the last few decades. The instability of food commodities price causes it to change rapidly over time. This paper attempts to develop Autoregressive Distributed Lag (ARDL) model in modeling and forecasting the price of palm oil.
Mohd Fahmi Abdul Hamid, Ani Shabri
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The long memory autoregressive distributed lag model and its application on Congressional approval [PDF]

Electoral Studies, 2010
This paper considers the instrumental variables (IV) estimation of the autoregressive distributed lag (ADL) model consisting of fractionally integrated regressors and errors, while allowing for part of the regressors to be endogenous. The idea of Liviatan (1963) and that of Tsay (2007) are combined to construct consistent and asymptotically normally ...
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