Informacja

Drogi użytkowniku, aplikacja do prawidłowego działania wymaga obsługi JavaScript. Proszę włącz obsługę JavaScript w Twojej przeglądarce.

English (EN)·Polski (PL)·Yкраїнський (UK)
Przejdź do strony domowej biblioteki Centralna Biblioteka Wojskowa Link otwiera się w nowym oknie Logo biblioteki Prolib Integro - strona głównaCentralna Biblioteka Wojskowa

Wyszukujesz frazę "Akpensuen, Shiaondo Henry" wg kryterium: Autor

  Lista filtrów
Wyrównaj
    Wyświetlanie 1-4 z 4
    Tytuł:
    Modeling the Impact of Agriculture, Export Earnings and Inflation on Gross Domestic Product Using the Generalized Least Square (GLS) Approach
    Autorzy:
    Akpensuen, Shiaondo Henry
    Joel, Simon
    Alhaji, Abdullahi Gwani
    Powiązania:
    https://bibliotekanauki.pl/articles/1059403.pdf
    Data publikacji:
    2019
    Wydawca:
    Przedsiębiorstwo Wydawnictw Naukowych Darwin / Scientific Publishing House DARWIN
    Tematy:
    Agriculture
    Export Earnings
    Gross Domestic Product (GDP)
    Inflation
    Opis:
    The paper explored the impact of Agriculture, export earnings and inflation on gross domestic product (GDP). Time series data were obtained from the central bank of Nigeria statistical bulletin from 1981 to 2018. Each series consist of 38 observations. Evidence from our study showed that the predictor variables (Agriculture, export earnings and inflation) were significantly joint predictors of Gross Domestic Product. The predictor variables jointly explained 68.958% of GDP. Result of the analysis also revealed that both agriculture and export earnings have a positive impact on gross domestic product reaffirming the importance of the sectors to economic growth while inflation has a negative impact on gross domestic product. With evidence that agriculture has the potential to cause economic growth, spur industrialization as well as to enhance the living condition of the nation’s majority, there should be increased investment in the development of the sector. This study also revealed that inflation is detrimental to sustainable economic growth in Nigeria. The result has important policy implications for both domestic policy makers and development partners. It also implies that controlling inflation is a necessary condition for promoting economic growth. Thus, policy makers should focus on maintaining inflation at a low rate probably single digit.
    Źródło:
    World Scientific News; 2019, 134, 2; 326-334
    2392-2192
    Pojawia się w:
    World Scientific News
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Time Series ARIMA Model for Predicting Nigeria Net Foreign Direct Investment (FDI)
    Autorzy:
    Akpensuen, Shiaondo Henry
    Edeghagba, Eghosa Elijah
    Alhaji, Abdullahi Gwani
    Joel, Simon
    Powiązania:
    https://bibliotekanauki.pl/articles/1059523.pdf
    Data publikacji:
    2019
    Wydawca:
    Przedsiębiorstwo Wydawnictw Naukowych Darwin / Scientific Publishing House DARWIN
    Tematy:
    ADF
    ARIMA
    Forecasting
    Foreign Direct Investment
    Nigeria
    Opis:
    This paper presents an empirical study of modelling and forecasting time series data of Nigeria net foreign direct investment (FDI). The Box-Jenkins ARIMA methodology was used for forecasting the yearly data collected from 1972 to 2018. Result of the analysis revealed that the series became stationary at first difference. The diagnostic checking has shown that ARIMA (1, 1, 2) is appropriate or optimal model based on the Akaike’s Information Criterion (AIC), the Bayesian Information Criterion (BIC) and Hannan Quinn criterion (HQ). A twenty (20) year forecast was made from 2019-2039, the result of the forecast showed that the net FDI in Nigeria will continue to grow in the period forecasted. These forecasts will help policy makers in Nigeria to sustain their efforts to expand the tax base, reduce red tape, and strengthen the regulatory framework to investment and also investors friendly policies in order to attract the much needed FDI.
    Źródło:
    World Scientific News; 2019, 128, 2; 348-362
    2392-2192
    Pojawia się w:
    World Scientific News
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Best Time Series In-sample Model for Forecasting Nigeria Exchange Rate
    Autorzy:
    Gaddafi, Adamu Babali
    Akpensuen, Shiaondo Henry
    Shitu, Abdulrazaq Ahmed
    Malle, Ahmad Atiku
    Adamu, Muhammed
    Bukar, Muhammad Goni
    Powiązania:
    https://bibliotekanauki.pl/articles/1031300.pdf
    Data publikacji:
    2021
    Wydawca:
    Przedsiębiorstwo Wydawnictw Naukowych Darwin / Scientific Publishing House DARWIN
    Tematy:
    ARIMA
    Autoregressive Integrated Moving Average Model
    Autoregressive Moving Average Model
    Autoregressive models
    Box-Jenkins Methodology
    CBN
    Exchange rate
    Model
    Moving Average Models
    Nigeria
    Opis:
    In this work we considered data on official Nigeria exchange rates (Naira to British Pound sterling) from January 2003 to December 2019. Four competing models ARIMA (1, 1, 1), ARIMA (2, 1, 1), ARIMA (1, 1, 0) and ARIMA (1, 1, 2) were identified for the exchange rates series. Diagnostic analysis revealed that all the competing models adequately represent the exchange rate series. However, on the basis of out-of-sample model selection and evaluation ARIMA (1, 1, 1) was selected as the optimal model with minimum information criteria for the exchange rate series. A 24 months forecast indicates that the Naira will continue to depreciate. The policy implication of our study is that the Central Bank of Nigeria (CBN), should devalue the Naira in order to not only re-establish exchange rate stability but also encourage local manufacturing and encourage foreign capital inflows.
    Źródło:
    World Scientific News; 2021, 151; 45-63
    2392-2192
    Pojawia się w:
    World Scientific News
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Application out-of-sample forecasting in model selection on Nigeria exchange rate
    Autorzy:
    Henry, Akpensuen Shiaondo
    Lasisi, K. E.
    Akpan, E. A.
    Gwani, A. A.
    Powiązania:
    https://bibliotekanauki.pl/articles/1062858.pdf
    Data publikacji:
    2019
    Wydawca:
    Przedsiębiorstwo Wydawnictw Naukowych Darwin / Scientific Publishing House DARWIN
    Tematy:
    ARMA model
    Exchange Rate
    In-sample forecasting
    Model selection and evaluation
    Out-sample forecasting
    Opis:
    In time series, several competing models may adequately fit a given set of data. At times choosing the best model may be easy or difficult. However, there are two major model selection criteria; it could be either in-sample or out-of-sample forecasts. This study was necessitated because Empirical evidence based on out-of-sample model forecast performance is generally considered more trustworthy than evidence based on in-sample model performance which can be more sensitive to outliers and data mining. And also the fact that Out-of-sample forecasts also better reflect the information available to the forecaster in real time was also an added motivation. Hence this study considered data from Nigeria exchange rate (Naira to US Dollar) from January 2002 to December 2018 comprising 204 observations. The first 192 observations were used for model identification and estimation while the remaining 12 observations were holdout for forecast validation. Three ARIMA models; ARIMA (0, 1, 1), ARIMA (1, 1, 2) and ARIMA (2, 1, 0) were fitted tentatively. Base on in-sample information criteria ARIMA (0, 1, 1) was the best model with minimum AIC, SIC and HQ information criteria. However, on the basics of out-of-sample forecast evaluation using RMSE, MSE, MAE, and MAPE, ARIMA (2, 1, 0) perform better than ARIMA (0, 1, 1). The implication of this study is that, a model that is best in the in-sample fitting may not necessary give a genuine forecasts since it is the same data that is used in model identification and estimation that is also use in forecast evaluation.
    Źródło:
    World Scientific News; 2019, 127, 3; 225-247
    2392-2192
    Pojawia się w:
    World Scientific News
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-4 z 4

      Ta witryna wykorzystuje pliki cookies do przechowywania informacji na Twoim komputerze. Pliki cookies stosujemy w celu świadczenia usług na najwyższym poziomie, w tym w sposób dostosowany do indywidualnych potrzeb. Korzystanie z witryny bez zmiany ustawień dotyczących cookies oznacza, że będą one zamieszczane w Twoim komputerze. W każdym momencie możesz dokonać zmiany ustawień dotyczących cookies