Academic literature on the topic 'ARDL: autoregressive distributed lag'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'ARDL: autoregressive distributed lag.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Journal articles on the topic "ARDL: autoregressive distributed lag"
1
Ponziani, Regi Muzio. "Inflation forecasting using autoregressive distributed lag (ARDL) models." Jurnal Ekonomi & Studi Pembangunan 24, no. 2 (2023): 316–30. http://dx.doi.org/10.18196/jesp.v24i2.17620.
Full textAbstract:
This study attempts to evaluate and compare the inflation-predicting performance of several ARDL models. Since there was no cointegration, the ARDL model does not employ an error correction term. Subsequently, model development showed that ARDL(2,2) should be used. Besides the formally developed model, some other more arbitrarily chosen ARDL models were also included, i.e., ARDL(1,1), ARDL(2,0), ARDL(1,0), ARDL(0,1), and ARDL(0,2). This research measures forecasting performance with inflation as the forecasting object. The duration of the monthly inflation statistics ranged from January 2011 to July 2022. The data were separated into two categories. The training data ranged between January 2011 and December 2021. After getting the appropriate parameters from the training data, the models generated projections from January 2022 to July 2022. The research determined that ARDL (1,0) was the most accurate inflation forecasting model, followed by ARDL (0,2) and formally constructed ARDL(2,2) finished in fourth place. This study suggests that the formal development of ARDL for forecasting purposes is unnecessary. Formal ARDL development is more appropriate for root cause analysis. In addition, the single autoregressive component indicates that most of the inflation value's information originated from the prior period. This suggests that the previous period's value is Indonesia's most significant predictor of inflation. The impact of greater period lags on inflation forecasting diminishes immediately.
2
Kripfganz, Sebastian, and Daniel C. Schneider. "ardl: Estimating autoregressive distributed lag and equilibrium correction models." Stata Journal: Promoting communications on statistics and Stata 23, no. 4 (2023): 983–1019. http://dx.doi.org/10.1177/1536867x231212434.
Full textAbstract:
We present a command, ardl, for the estimation of autoregressive distributed lag (ARDL) models in a time-series context. The ardl command can be used to fit an ARDL model with the optimal number of autoregressive and distributed lags based on the Akaike or Bayesian (Schwarz) information criterion. The regression results can be displayed in the ARDL levels form or in the error-correction representation of the model. The latter separates long-run and short-run effects and is available in two different parameterizations of the long-run (cointegrating) relationship. The popular bounds-testing procedure for the existence of a long-run levels relationship is implemented as a postestimation feature. Comprehensive critical values and approximate p-values obtained from response-surface regressions facilitate statistical inference.
3
Handoyo, Samingun, Ying-Ping Chen, Tiara Mawidha Shelvi, and Heni Kusdarwati. "Modeling Vector Autoregressive and Autoregressive Distributed Lag of the Beef and Chicken Meat Prices during the Covid-19 Pandemic in Indonesia." Journal of Hunan University Natural Sciences 49, no. 3 (2022): 220–31. http://dx.doi.org/10.55463/issn.1674-2974.49.3.25.
Full textAbstract:
The impact of the COVID-19 pandemic has spread to all aspects of life. Modeling the price of beef and chicken meat is very important for the government to avoid extreme fluctuations of both commodities in the prices so that society's purchasing power can be maintained. This study has several objectives, namely building VAR and ARDL models from multiple time series data (beef and chicken meat prices), conducting variable selection with forwarding subset selection on input lag in the ARDL model, and measuring the performance of the VAR and ARDL models on the both of beef and chicken meat prices based on the value of RMSE, MAE, and R_square both in the training and testing set. The novelty in this study is to propose an identification method for the lag inputs of the ARDL model based on the criteria of both the Alkaide Information criteria (AIC) value and the adjusted R square value by visualizing both criteria for all possible amounts of lag inputs. The results of the identification of the VAR model structure using the conventional method in time series modeling are yielded the different lag inputs that are compared to the ARDL model structure with lag inputs identified by using the proposed method. The ARDL model of the beef and chicken meat prices has better performance than the VAR model both on training and testing sets. In addition, the resulting VAR model also clearly shows the occurrence of overfitting problems.
4
Siti Afifatul Farichah. "ANALISIS INFLASI DI INDONESIA: PENDEKATAN AUTOREGRESSIVE DISTRIBUTED LAG (ARDL)." Jurnal Cakrawala Ilmiah 1, no. 10 (2022): 2467–84. http://dx.doi.org/10.53625/jcijurnalcakrawalailmiah.v1i10.2577.
Full textAbstract:
Inflasi diartikan sebagai sebuah peristiwa kenaikan harga beberapa barang dan jasa dimana kenaikan ini terjadi secara berkepanjangan secara umum dari tahun ke tahun. Pemerintah memiliki tujuan jangka Panjang berkaitan dengan Inflasi untuk menjaga kestabilan besarnya inflasi agar tetap stabil pada tingkat nilai yang rendah. Adanya permasalahan inflasi akan berdampak secara langsung terhadap pertumbuhan ekonomi. Pada penelitian ini, penulis hendak mengaanalisis adanya pengaruh Jumlah Uang beredar dan Indeks Harga Konsumen terhadap inflasi di Indonesia. Penelitian ini menggunakan metode penelitian kuantitatif, yaitu sebuah penelitian dimana dalam praktiknya dilakukan dengan menggunakan data sekunder yang diperoleh dari publikasi oleh pihak lain pada suatu kurun waktu tertentu. Sedangkan model yang diterapkan dalam penelitian ini merupakan model Autoregressive Distributed Lag (ARDL). ARDL merupakan salah satu model regresi dimana dalam praktiknya dilakukan dengan menambahkan adanya nilai variabel yang mampu mendiskripsikan nilai masa masa lalu atau nilai masa kini dari variable independen. Berdasarkan hasil estimasi dalam penelitian ini mengindikasikan bahwa terdapat adanya kointegrasi diantara variabel yang digunakan dan model yang didapatkan dari hasil estimasi yang menunjukkan dimana Variabel Jumlah Uang Beredar dan Indeks Harga Konsumen mengindikasikan adanya pengaruh yang signifikan terhadap terjadinya Inflasi di Indonesia baik pada jangka panjang maupun jangka pendek
5
Bhowmik, Debesh. "Indian Fiscal Deficit in Autoregressive Distributed Lag (ARDL) Model." Advancement in Management and Technology 05, no. 04 (2025): 01–15. https://doi.org/10.46977/amt.2025.v05i04.001.
Full textAbstract:
In this paper the author showed the trends of fiscal deficit and examined the short run and the long run nexus between fiscal deficit and gross domestic product per capita, inflation rate (CPI), external debt (% of GDP), unemployment rate (% of labour force), income inequality (income share difference between top 10% and bottom 50%), and military expenditure, respectively, during 1950-51-2023-24 in India by applying Auto Regressive Distributed Lag model. The paper found that the fiscal deficit contains a quadratic trend and denoised wavelet shrinkage. Automatically selected ARDL (3,0,2,3,0,0,3) model, where Akaike Information Criterion (AIC) is minimum, showed that the fiscal deficit is positively associated with inflation and negatively related with debt and per capita GDP significantly in the long run while positively related with inflation and debt and negatively related with military expenditure in the short run significantly. The cointegrating equation states that inflation and debt are directly related and GDP per capita is inversely related to fiscal deficit, and it is converging towards equilibrium at the speed of adjustment of 92% per annum significantly. Unemployment and income inequality have a positive impact on the fiscal deficit in the short and long run insignificantly. The model is stable and contains no serial correlation but contains heteroscedasticity and non-normality. The model demands expenditure-reducing policies in non-plan and defence expenditure, as well as employment and poverty amelioration-oriented fiscal financing at a threshold limit, to achieve sustainable economic growth.
6
Efendi, Achmad, Yusi Tyroni Mursityo, Ninik Wahju Hidajati, Nur Andajani, Zuraidah Zuraidah, and Samingun Handoyo. "Multiple Time Series Modeling of Autoregressive Distributed Lags with Forward Variable Selection for Prediction." WSEAS TRANSACTIONS ON BUSINESS AND ECONOMICS 21 (April 19, 2024): 1012–26. http://dx.doi.org/10.37394/23207.2024.21.84.
Full textAbstract:
The conventional time series methods tend to explore the modeling process and statistics tests to find the best model. On the other hand, machine learning methods are concerned with finding it based on the highest performance in the testing data. This research proposes a mixture approach in the development of the ARDL (Autoregressive Distributed Lags) model to predict the Cayenne peppers price. Multiple time series data are formed into a matrix of input-output pairs with various lag numbers of 3, 5, and 7. The dataset is normalized with the Min-max and Z score transformations. The ARDL predictor variables of each lag number and dataset combinations are selected using the forward selection method with a majority vote of four criteria namely the Cp (Cp Mallow), AIC (Akaike Information Criterion), BIC (Bayesian Information Criterion), and adjusted R2 . Each ARDL model is evaluated in the testing data with performance metrics of the RMSE (Root Mean Square Error), MAE (Mean Absolute Error), and R2 . Both AIC and adjusted R2 always form the majority vote in the determining optimal predictor variable of ARDL models in all scenarios. The ARDL predictor variables in each lag number are different but they are the same in the different dataset scenarios. The price of Cayenne pepper yesterday is the predictor variable with the most contribution in all of the 9 ARDL models yielded. The ARDL lag 3 with the original dataset outperforms in the RMSE and MAE metrics while the ARDL lag 3 with the Z score dataset outperforms in the R2 metric.
7
Ningrum, Dewi Kusuma, and Sugiyarto Surono. "Comparison the Error Rate of Autoregressive Distributed Lag (ARDL) and Vector Autoregressive (VAR) (Case study: Forecast of Export Quantities in DIY)." JURNAL EKSAKTA 18, no. 2 (2018): 167–77. http://dx.doi.org/10.20885/eksakta.vol18.iss2.art8.
Full textAbstract:
Forecasting is estimating the size or number of something in the future. Regression model that enters current independent variable value, and lagged value is called distributed-lag model, if it enters one or more lagged value, it is called autoregressive. Koyck method is used for dynamic model which the lagged length is unknown, for the known lagged length it is used the Almon method. Vector Autoregressive (VAR) is a method that explains every variable in the model depend on the lag movement from the variable itself and all the others variable. This research aimed to explain the application of Autoregressive distributed-lag model and Vector Autoregressive (VAR) method for the forecasting for export amount in DIY. It takes export amount in DIY and inflation data, kurs, and Indonesias foreign exchange reserve. Forecasting formation: defining Koyck and Almon distributed-lag dynamic model, then the best model is chosen and distribution-lag dynamic forecasting is performed. After that it is performed stationary test, co-integration test, optimal lag examination, granger causality test, parameter estimation, VAR model stability, and performs forecasting with VAR method. The forecasting result shows MAPE value from ARDL method obtained is 0.475812%, while MAPE value from VAR method is 0.464473%. Thus it can be concluded that Vector Autoregressive (VAR) method is more effective to be used in case study of export amount in DIY forecasting. Keywords: Koyck; Almon; Lag; Autoregressive Distributed-Lag; Vector Autoregressive;
8
Abedi, Ali, Mohammad Mousavi Baygi, Parinaz Poursafa, et al. "Air pollution and hospitalization: an autoregressive distributed lag (ARDL) approach." Environmental Science and Pollution Research 27, no. 24 (2020): 30673–80. http://dx.doi.org/10.1007/s11356-020-09152-x.
Full text
9
Sukmana, Rania, Tarno Tarno, and Puspita Kartikasari. "PEMODELAN AUTOREGRESSIVE DISTRIBUTED LAG UNTUK MEMPREDIKSI NILAI IMPOR NON-MIGAS DI INDONESIA." Jurnal Gaussian 13, no. 2 (2025): 499–508. https://doi.org/10.14710/j.gauss.13.2.499-508.
Full textAbstract:
The International Monetary Fund warns countries about the global economic recession in 2023. Efforts required from policy makers to prevent a recession. A deficit balance of payments shows signs of recession because the rate of imports is higher than exports. The highest import value over the last decade is non-oil and gas commodities. Factors affecting imports include exchange rates, prices of goods, and consumer income. Import activities require proper studies to make policies so that research is needed, one of which is by using the Autoregressive Distributed Lag (ARDL) method. ARDL is a regression model in which the independent variable consists of the current and past independent variable values and the past values of the dependent variable. The data used is from the first quarter of 2008 to the fourth quarter of 2022. The model formed is ARDL(3,2,2,1). The current non-oil and gas import is positively affected by the non-oil and gas imports at lag one, three, and four, as well as the exchange rate at lag three and is negatively affected by the non-oil and gas import and the exchange rate at lag two. The accuracy of forecasting with sMAPE is 12,12%, which means the forecast is accurate.
10
Kriskkumar, Karunanithi, Niaz Ahmad Mohd Naseem, and Wan Ngah Wan Azman-Saini. "Investigating the Asymmetric Effect of Oil Price on the Economic Growth in Malaysia: Applying Augmented ARDL and Nonlinear ARDL Techniques." SAGE Open 12, no. 1 (2022): 215824402210799. http://dx.doi.org/10.1177/21582440221079936.
Full textAbstract:
This paper attempts to investigate if the effect of oil price on growth is asymmetrical for Malaysia, a small-open-dynamic oil-exporting country, over a period from 1981 to 2017. The empirical method employed in this study is the augmented autoregressive distributed lag model (ARDL) bound test approach and the recent innovative nonlinear autoregressive distributed lag (NARDL) model. Results suggest that neglecting nonlinearities can lead to misleading results. More precisely, the result reveals that adjustments in the price of oil influence Malaysia’s economic growth asymmetrically. An increase and decrease in the price of oil strengthen the economic growth of Malaysia, demonstrating Malaysia’s ability to be both an oil-producing country and a trading nation. These results strongly imply that Malaysia is able to take advantage of changes in the oil price efficiently.
Dissertations / Theses on the topic "ARDL: autoregressive distributed lag"
1
Laniran, Temitope J. "Impact of state fragility on capital flows and economic growth in Nigeria." Thesis, University of Bradford, 2018. http://hdl.handle.net/10454/17218.
Full textAbstract:
This thesis aims to investigate the impact of state fragility on capital inflows and economic growth in Nigeria over the period 1980-2015. In line with existing studies, it adopts an augmented neoclassical growth model where capital is divided into domestic and foreign capital inflows (FDI, ODA and Remittances). Using an autoregressive distributed lag (ARDL) bounds testing approach to co-integration, significant long-run relationship was confirmed between state fragility, capital flows and economic growth. The results reveal domestic capital to be very significant and contribute positively to economic growth. Similarly it was observed that remittances remain a very crucial form of capital flow to Nigeria and that the presence of state fragility makes it more significant. For ODA a positive contribution to economic growth was observed, however, the presence of state fragility renders it insignificant. In the case of FDI, the study found a negative relationship between FDI and economic growth albeit insignificant. However, the presence of state fragility makes it significant but still negative. A negative relationship was also observed between state fragility and economic growth. These findings, implies that while the issue of state fragility needs to be addressed and concerted efforts put into building state resilience, not just for the direct impact of state fragility on the economy, but also its impact on the economy through other channels such as capital flows.
2
Bakin, Bilge. "The Causal Relationships Among Economic Growth, Foreign Direct Investment And Financial Sector Development In East Asian Countries: An Ardl Approach." Master's thesis, METU, 2011. http://etd.lib.metu.edu.tr/upload/12613256/index.pdf.
Full textAbstract:
The main purpose of the study is to examine the cointegration relationships among economic growth, foreign direct investment and financial sector development in 4 East Asian countries, namely Korea, Malaysia, the Philippines and Thailand between the years 1971-2008 by autoregressive distributed lag (ARDL) approach.
In the existing literature, there is no study examining the causal relationships among economic growth, foreign direct investment and financial sector development by applying ARDL methodology for these East Asian countries. The contribution of this study to the literature, the cointegration relationships are constructed to observe the direct linkage among these variables by ARDL approach. If cointegration relationships exist among these variables, then the effect of each regressor on the dependent variable is also investigated. The results of the study indicate that foreign direct investment and financial sector development could be long run forcing variables of economic growth. Additionally, economic growth and financial sector development could be long run forcing variables of foreign direct investment. However, there is not sufficient evidence that economic growth and foreign direct investment together are long run key determinants of financial sector development in a country as obtained in this study.
3
Torres, Luís Filipe Nunes Pardal Esteves. "Modelling the demand for military expenditure in Portugal." Master's thesis, Instituto Superior de Economia e Gestão, 2013. http://hdl.handle.net/10400.5/6540.
Full textAbstract:
Mestrado em Economia<br>Throughout history, countries from all over the world have devoted a considerable amount of resources to produce security. This evidence has motivated a growing number of studies that examine the determinants of the demand for military expenditure. Albeit the difficulty to develop a general theoretical framework and the inexistence of a standard empirical approach to model the demand for military expenditure, it is an important issue to understand which factors may influence the military expenditure demand function of a country.
The aim of this dissertation is to find out the main variables affecting the Portuguese military expenditure taking into account a comprehensive set of economic, strategic and political determinants. For this goal, a military expenditures demand model is constructed for the period 1960–2010 employing the Autoregressive Distributed Lag (ARDL) bound testing cointegration approach.
The results suggest that the Portuguese defence spending is determined by the country´s economic performance, allies‟ defence speeding and security considerations. As far as the domestic political environment is concerned, the dominant ideology of the party in power seems to be insignificant, while the transition to a democratic regime is considered a relevant determinant with a negative effect on the military expenditure.<br>Ao longo da história, países de todo o mundo têm empenhado uma quantidade considerável de recursos para produzir segurança. Esta constatação tem motivado um número crescente de estudos sobre as possíveis variáveis explicativas da despesa militar. Apesar da dificuldade em estabelecer um quadro teórico de referência e da inexistência de uma abordagem empírica padronizada para determinar a procura de despesa militar, revela-se importante compreender quais as variáveis que influenciam a despesa militar de um país.
O objetivo deste trabalho é aferir quais as principais fatores que poderão determinar a despesa militar de Portugal, tendo em conta um amplo conjunto de variáveis de natureza económica, estratégica e política. A prossecução deste objetivo assenta na construção de uma equação de procura para a despesa militar portuguesa, para o período compreendido entre 1960 e 2010, através de um modelo uniequacional ARDL.
Os resultados obtidos sugerem que a despesa militar em Portugal é determinada pelo desempenho económico, pelo gasto militar de países aliados e por considerações relativas à perceção das condições de segurança. No que respeita à influência do ambiente político, a ideologia dominante do partido em funções no Governo surge como não significante, ao passo que a transição para um regime democrático é considerada uma variável relevante, com um efeito negativo sobre as despesas militares.
4
Larsson, Rasmus, and Sebastian Haq. "The dynamics of stock market returns and macroeconomic indicators: An ARDL approach with cointegration." Thesis, KTH, Entreprenörskap och Innovation, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-189993.
Full textAbstract:
Macroeconomic indicators are amongst the most important and used tools for investors as they provide an outlook for the economy and thus improve the assessment of investments e.g. for asset allocation. The purpose of this thesis is to investigate the short- and long-run relationship between the US stock market index S&P500 and six selected macroeconomic indicators during different time regimes during 2000-2016. The chosen indicators are Personal spending, Initial jobless claims, M1 Money supply, Building permits, Michigan Consumers Sentiment index and the ISM Manufacturing index as they measure different parts of the economy and are commonly used by investors. We achieve the purpose by using the Autoregressive Distributed Lags model (ARDL) as it has several advantages in relation to comparable time series models. The results show that all indicators except Personal spending are significant in the long-run on the 1-percent level, in at least one time-regime. All indicators have significant results also in the short-run except the Money Supply (M1), depending on which time period that is under investigation. Our conclusion is that our chosen indicators have different characteristics depending on the current dynamics of the stock market, economic state and other related markets. The practical implication for investors is that different indicators are of limited use depending on the current market dynamics and investors must evaluate the underlying premises of the development of the indicator rather than interpreting a specific datapoint.<br>Makroekonomiska indikatorer är bland de mest viktiga och använda verktygen av investerare eftersom man kan få en överblick av den ekonomiska utvecklingen och således förbättra beslutsunderlaget vid till exempel tillgångsallokering. Syftet med denna avhandling är att undersöka de kort- och långsiktiga förhållandena mellan det amerikanska aktiemarknadsindexet S&P500 och sex utvalda makroekonomiska indikatorer under olika tidsperioder mellan 2000-2016. De valda indikatorerna är Personal spending, Initial jobless claims, M1 Money supply, Building permits, Michigan Consumers Sentiment index och ISM Manufacturing index eftersom de mäter olika delar av ekonomin och används kontinuerligt av investerare. Vi uppnår syftet genom att använda en Autoregressive Distributed Lags (ARDL) modell då den har flertalet fördelar i förhållande till jämförbara tidsseriemodeller. Resultaten visar att alla indikatorer utom Personal spending är signifikant på lång sikt på enprocentsnivån, över olika tidsperioder. Alla indikatorer har även signifikanta resultat på kort sikt förutom M1 Money supply, beroende på vilken tidsperiod som studeras. Vår slutsats är att dem valda indikatorerna har olika egenskaper beroende på den aktuella dynamiken i aktiemarknaden, ekonomin eller andra relaterade marknader. Den praktiska konsekvensen för investerare är att eftersom olika indikatorer är av begränsad användning beroende på den rådande marknadsdynamiken, måste investeraren noggrant utvärdera de underliggande villkoren för utvecklingen av en unik indikator snarare än att endast tolka en unik datapunkt.
5
Erdem, Fatma Pinar. "Business Cycles In Emerging Economies." Phd thesis, METU, 2011. http://etd.lib.metu.edu.tr/upload/12613853/index.pdf.
Full textAbstract:
Until very recently, most emerging market economies have achieved higher growth rates for the last decade. It is controversial whether this good economic environment
is due to domestic reforms or due to favorable external factors. In this framework, the main aim of this study is to investigate the structure and sources of business cycles in emerging market economies and to determine how these cycles differ than
those in developed countries. The role of external and domestic factors on business cycles are analyzed by applying not only the conventional panel data estimations but also common correlated effects panel mean group method which is introduced by Peseran (2006). Besides, the convergence of business cycles in emerging market economies to the business cycles in developed countries is discussed based on factor analysis. The major results indicate the common global factors are the leading source of the business cycles both in emerging market economies and developed countries. However, domestic determinants of fluctuations differ across two groups of countries. In addition, results show that in the last two decades fluctuations in emerging market economies have started to be more dependent on the fluctuations in developed countries.
6
Sagir, Serhat. "Effects Of Monetary Policy On Banking Interest Rates: Interest Rate Pass-through In Turkey." Master's thesis, METU, 2011. http://etd.lib.metu.edu.tr/upload/12613717/index.pdf.
Full textAbstract:
In this study, the effects of CBRT monetary policy decisions on the consumer, automobile, housing and commercial loans of the banks during the period from the early of 2004 to the middle of 2011 are examined. In order to perform this study, it is benefited from weekly weighted average loan interest rate data of the banks, which is the data having the highest frequency that could be obtained from the electronic data distribution system of CBRT.
Monetary policy instruments of Central Bank may change in the course of time or monetary policy could be executed by more than one instrument. Therefore, as the political interest rate would be insufficient in the calculation of the effect of monetary policy on loan interest rates of the banks, Government Dept Securities&rsquo<br>premiums are used instead of the political interest rates in this study to make it reflect the policies of central bank more clearly as a whole. Among the Government Dept Securities that have different maturity structure, benchmark bonds that are adapted to the expected political interest rate changes and that react to the unexpected interest rate changes at the high rate (reaction coefficient 0.983) are used.
In order to weight the cointegration relation between interest rates, unrestricted error correction model is established and it is determined by Bound Test that there is a long-term relation between each interest rate and interest rate of benchmark bond. After a cointegration relation is determined among the serials, autoregressive distributed lag model is used to determine the level of transitivity and it is determined that monetary policy decisions affect the banking interest rate at 77% level and by 13 weeks delay on average.
7
Ferdi, Fouad. "Dynamique macroéconomique des firmes financiarisées." Thesis, Sorbonne Paris Cité, 2019. http://www.theses.fr/2019USPCD006.
Full textAbstract:
La question principale de ce travail de recherche est de déterminer le type du régime de croissance économique des pays dits « avancés ». Pour ce faire, j’étudie le schéma d’accumulation du capital au travers du comportement d’investissement des entreprises non financières, afin d’en établir les conséquences en termes de stabilité économique. Je défends l'idée d'une instauration depuis les années 1980 d'un régime de croissance basé, entre autres, sur le capital intangible et financier, dont j'étudie les caractéristiques et les conséquences sur l'économie. A partir de cette hypothèse, je propose de réviser la théorie du profit d’Adrian Wood (1975) à l’aune de ces transformations institutionnelles récentes, afin d’éclairer les dynamiques méso économiques d’accumulation de capital au sein des grandes firmes multinationales. Cette nouvelle vision de la firme financiarisée et mondialisée, est ensuite confrontée à la théorie d’instabilité financière de Hyman Minsky afin d’apporter des éléments de réponse à la problématique de départ. La croissance induite par ces nouveaux comportements d’investissement et de financement peut-elle s’inscrire dans l’approche minskyenne d’une croissance intrinsèquement instable ? La démarche consiste à établir un lien entre, d’une part, les stratégies d’accumulation du capital global (fixe, financier et intangible) et le levier d’endettement des entreprises avec, d’autre part, les conséquences macroéconomiques de la dynamique d’endettement sur la croissance globale<br>The main goal of this thesis was to determine the macroeconomic growth regime of advanced economies. Hence, I addressed the non-financial corporation’s capital accumulation schemes in order to establish their macrodynamics as regard to stability issues. It has been argued that the financialization phenomenon has deeply transformed the growth path by changing NFCs’ habits of investment. Following two major institutional mutations, big multinational firms adapted their investment funding process according to the transformation of the international financial system. They increasingly engaged into financial activities to guaranty a better access to capital next to a better short-run profitability for the sake of shareholders’ value maximization. Their financial holding entities, acting as cash hubs, invested in the excess securities resulting from banks’ new paradigm in dealing with debt, i.e. “generate and distribute”. From another stand, another institutional change affected the production process towards the paradigm of “downsize and distribute”. At the end of the day, to stand steady over these two mutating legs (namely production and its funding) NFCs had to keep control over both. From one side, they engaged into intangibles to lead the global value chain and control production, and from the other, into financial investment to optimize their funding capacity
8
Chetty, Roheen. "An Analysis of the Finance Growth Nexus in Nigeria." Master's thesis, Faculty of Commerce, 2021. http://hdl.handle.net/11427/33430.
Full textAbstract:
This study empirically examines the relationship between financial development and economic growth in Nigeria. It employs statistical techniques such as the Autoregressive Distributed Lag approach as well as a short and long run Granger Causality test on time series data spanning from 1960-2016. Empirical results reveal that the financial development indicators have a long run relationship with economic growth in Nigeria and the existence of unidirectional and bidirectional Granger causality was also discovered. This study recommends that policy should be geared towards promoting financial development in the country as well as encouraging more financial depth and openness – in order to foster economic growth in Nigeria.
9
Olfati, Ronak. "The Impact of Oil Revenue on the Iranian Economy." Thesis, University of Bradford, 2018. http://hdl.handle.net/10454/16834.
Full textAbstract:
This study aims to identify the effects of oil income on economic growth in Iran over the period 1955-2014. The empirical literature indicates that countries with natural resources are growing more slowly than their counterparts. However, the results from this literature are far from conclusive, particularly in regard to the role played by oil-rich countries. Needless to say, this role depends on other factors as well, including the political situation in the country, the quality of institutions, and the efficacy of the financial system. Some empirical research has found that natural resources, particularly oil, can have a positive impact on the output of a country. although natural resources are not a factor of production in growth theories, studies have used different growth frameworks in order to discover whether having natural resources is a blessing or a curse. In line with recent studies, this work uses an augmented neoclassical growth model to develop a theoretical framework where oil enters the long-term output of the country through saving and investment. Overall, the results suggests that oil income has a positive impact on the level of output per capita in Iran. The findings of the econometric results are in line with the historical analysis of the study. Since different methods and proxies were used, a total of eight models were estimated. Interestingly, when PRIVY is used as an index of financial development, the result of the study changes and oil no longer has a significant impact on the economy. However, this can be translated to an inefficient allocation of credit to the private sector.
10
Louw, Riëtte. "Forecasting tourism demand for South Africa / Louw R." Thesis, North-West University, 2011. http://hdl.handle.net/10394/7607.
Full textAbstract:
Tourism is currently the third largest industry within South Africa. Many African countries, including
South Africa, have the potential to achieve increased economic growth and development with the aid of
the tourism sector. As tourism is a great earner of foreign exchange and also creates employment
opportunities, especially low–skilled employment, it is identified as a sector that can aid developing
countries to increase economic growth and development. Accurate forecasting of tourism demand is
important due to the perishable nature of tourism products and services. Little research on forecasting
tourism demand in South Africa can be found. The aim of this study is to forecast tourism demand
(international tourist arrivals) to South Africa by making use of different causal models and to compare
the forecasting accuracy of the causal models used. Accurate forecasts of tourism demand may assist
policy–makers and business concerns with decisions regarding future investment and employment.
An overview of South African tourism trends indicates that although domestic arrivals surpass foreign
arrivals in terms of volume, foreign arrivals spend more in South Africa than domestic tourists. It was
also established that tourist arrivals from Africa (including the Middle East), form the largest market of
international tourist arrivals to South Africa. Africa is, however, not included in the empirical analysis
mainly due to data limitations. All the other markets namely Asia, Australasia, Europe, North America,
South America and the United Kingdom are included as origin markets for the empirical analysis and
this study therefore focuses on intercontinental tourism demand for South Africa.
A review of the literature identified several determinants of tourist arrivals, including income, relative
prices, transport cost, climate, supply–side factors, health risks, political stability as well as terrorism
and crime. Most researchers used tourist arrivals/departures or tourist spending/receipts as dependent
variables in empirical tourism demand studies.
The first approach used to forecast tourism demand is a single equation approach, more specifically an
Autoregressive Distributed Lag Model. This relationship between the explanatory variables and the
dependent variable was then used to ex post forecast tourism demand for South Africa from the six
markets identified earlier. Secondly, a system of equation approach, more specifically a Vector
Autoregressive Model and Vector Error Correction Model were estimated for each of the identified six
markets. An impulse response analysis was undertaken to determine the effect of shocks in the
explanatory variables on tourism demand using the Vector Error Correction Model. It was established that it takes on average three years for the effect on tourism demand to disappear. A variance
decomposition analysis was also done using the Vector Error Correction Model to determine how each
variable affects the percentage forecast variance of a certain variable. It was found that income plays an
important role in explaining the percentage forecast variance of almost every variable. The Vector
Autoregressive Model was used to estimate the short–run relationship between the variables and to ex
post forecast tourism demand to South Africa from the six identified markets.
The results showed that enhanced marketing can be done in origin markets with a growing GDP in
order to attract more arrivals from those areas due to the high elasticity of the real GDP per capita in the
long run and its positive impact on tourist arrivals. It is mainly up to the origin countries to increase
their income per capita. Focussing on infrastructure development and maintenance could contribute to
an increase in future tourist arrivals. It is evident that arrivals from Europe might have a negative
relationship with the number of hotel rooms available since tourists from this region might prefer
accommodation with a safari atmosphere such as bush lodges. Investment in such accommodation
facilities and the marketing of such facilities to Europeans may contribute to an increase in arrivals from
Europe. The real exchange rate also plays a role in the price competitiveness of the destination country.
Therefore, in order for South Africa to be more price competitive, inflation rate control can be a way to
increase price competitiveness rather than to have a fixed exchange rate.
Forecasting accuracy was tested by estimating the Mean Absolute Percentage Error, Root Mean Square
Error and Theil’s U of each model. A Seasonal Autoregressive Integrated Moving Average (SARIMA)
model was estimated for each origin market as a benchmark model to determine forecasting accuracy
against this univariate time series approach. The results showed that the Seasonal Autoregressive
Integrated Moving Average model achieved more accurate predictions whereas the Vector
Autoregressive model forecasts were more accurate than the Autoregressive Distributed Lag Model
forecasts. Policy–makers can use both the SARIMA and VAR model, which may generate more
accurate forecast results in order to provide better policy recommendations.<br>Thesis (M.Com. (Economics))--North-West University, Potchefstroom Campus, 2011.
Books on the topic "ARDL: autoregressive distributed lag"
1
Pesaran, Hashem. An autoregressive distributed lag modelling approach to cointegration analysis. Department of Applied Economics, University of Cambridge, 1995.
Find full textBook chapters on the topic "ARDL: autoregressive distributed lag"
1
Phong, Le Hoang, Ho Hoang Gia Bao, and Dang Thi Bach Van. "Testing J-Curve Phenomenon in Vietnam: An Autoregressive Distributed Lag (ARDL) Approach." In Econometrics for Financial Applications. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-73150-6_39.
Full text
2
Slesman, Ly. "Natural Resource Rents and Economic Development: Evidence from Brunei Darussalam." In Asia in Transition. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-97-6926-1_3.
Full textAbstract:
Abstract This chapter examines Brunei Darussalam’s economic development from the perspective of an oil and gas-dependent economy. First, using relevant socio-economic indicators, it assesses the economic structures, tracing their evolution to their current forms, the dynamics of Brunei’s reliance on the oil and gas sector, and the relative importance of the non-oil and gas sector in its economic progress. Is Brunei’s experience with oil and gas dependency in line with the ‘resource curse’ or ‘resource blessing’ viewpoints? What do the data say? The analysis provides answers to these questions by quantifying short- and long-run effects of oil and gas rents on economic growth over the 1970–2019 period using the dynamic time series econometric modelling framework of the autoregressive distributed lag (ARDL) model. Given the importance of economic diversification in achieving Wawasan Brunei 2035 (Brunei Vision 2035), the chapter further discusses its progress and challenges.
3
Alexander, Rhoda, and Husam Aldin Al-Malkawi. "The Impact of Macroeconomic Factors on the Nifty Auto Index." In Lecture Notes in Civil Engineering. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-27462-6_2.
Full textAbstract:
AbstractThe aim of the paper is to investigate the association between selected macroeconomic variables like crude price, exchange rate, index of industrial production, inflation, interest rate, repo rate, gold price and the auto index of the National Stock Exchange (NSE) of India during a time when the automotive sector in India witnessed the sharpest dip in sales. The study adopts Autoregressive Distributed Lag (ARDL) co-integration approach and performs suitable diagnostic tests. Results indicate that, exchange rate has a significant negative relationship with Nifty auto index in the long run. Additionally, crude price, index of industrial production and repo rates are statistically significant determinants of Nifty auto index. On the contrary, first lag of crude price is found to be a possible predictor of the index in the short run. The study provides important implications for researchers, corporations, portfolio managers, investors, and government. Despite the availability of a large body of literature exploring the association between macro-economic factors and stock market in India, research exploring the association between the former and Indian auto indices has been sparse. Hence, this study is intended to fill this gap in the literature.
4
Rahmouni, Abdelwahab, Mohamed Meddi, and Hafsa Karahaçane. "Modeling and Forcasting of Surface Runoff in the Beni Bahdel Dam: Using ARDL Model (Autoregressive Distributed Lag)." In Recent Advances in Environmental Science from the Euro-Mediterranean and Surrounding Regions. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-70548-4_241.
Full text
5
Parly, Haidah Syafi, Siti Meriam Zahari, Muhammad Asmu’i Abdul Rahim, and S. Sarifah Radiah Shariff. "An Autoregressive Distributed Lag (ARDL) Analysis of the Relationships Between Employees Provident Fund’s Wealth and Its Determinants." In Communications in Computer and Information Science. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-7334-4_16.
Full text
6
Ha, Nguyen Thi Vinh. "Evaluating Impact of Climate Change to Fishing Productivity of Vietnam: An Application of Autoregressive Distributed Lag (ARDL) Regression Model." In Global Changes and Sustainable Development in Asian Emerging Market Economies Vol. 2. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-81443-4_43.
Full text
7
Liu, Anyu, and Xinyang Liu. "The autoregressive distributed lag model." In Econometric Modelling and Forecasting of Tourism Demand. Routledge, 2022. http://dx.doi.org/10.4324/9781003269366-3.
Full text
8
Phong, Le Hoang, Dang Thi Bach Van, and Ho Hoang Gia Bao. "A Nonlinear Autoregressive Distributed Lag (NARDL) Analysis on the Determinants of Vietnam’s Stock Market." In Beyond Traditional Probabilistic Methods in Economics. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-04200-4_27.
Full text
9
Puntoon, Wiranya, Payap Tarkhamtham, and Woraphon Yamaka. "The Effects of Oil Shocks on Inflation in Leading Crude Oil Importing Countries: Non-linear Autoregressive Distributed Lag." In Machine Learning for Econometrics and Related Topics. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-43601-7_23.
Full text
10
Rahmadi, Saiful, Rosnawintang, Ernawati, Aini Indridjawati, and Burhanuddin. "The Effect of State Openness and Institutional Economy on Economic Growth in ASEAN Countries: An Application of Autoregressive Distributed Lag Model." In Proceedings of the 7th International Conference on Accounting, Management and Economics (ICAME-7 2022). Atlantis Press International BV, 2023. http://dx.doi.org/10.2991/978-94-6463-146-3_65.
Full textConference papers on the topic "ARDL: autoregressive distributed lag"
1
Mittal, Amit, Somesh Sharma, Shweta Arora, Prakash Garia, and Pradeep Kumar Sharma. "Assessing Water Dissolved Oxygen Dynamics: Autoregressive Distributed Lag (ARDL) Approach for Environmental Sustainability." In 2024 8th International Conference on Inventive Systems and Control (ICISC). IEEE, 2024. http://dx.doi.org/10.1109/icisc62624.2024.00099.
Full text
2
Hamid, Mohd Fahmi Abdul, and Ani Shabri. "Palm oil price forecasting model: An autoregressive distributed lag (ARDL) approach." In THE 3RD ISM INTERNATIONAL STATISTICAL CONFERENCE 2016 (ISM-III): Bringing Professionalism and Prestige in Statistics. Author(s), 2017. http://dx.doi.org/10.1063/1.4982864.
Full text
3
Fitri, Fadhilah, Toni Toharudin, and I. Gede Nyoman Mindra Jaya. "Marine capture fisheries production and intensity of rainfall: An application of autoregressive distributed lag (ARDL) model." In STATISTICS AND ITS APPLICATIONS: Proceedings of the 2nd International Conference on Applied Statistics (ICAS II), 2016. Author(s), 2017. http://dx.doi.org/10.1063/1.4979454.
Full text
4
Atsi, Eugene Ray. "OIL PRICES, EXCHANGE RATE VOLATILITY AND FDI INFLOWS ON THE ECONOMIC GROWTH OF GHANA: WAVELET TECHNIQUE AND ARDL APPROACH." In MBP 2025 Tokyo International Conference on Management & Business Practices, 21-22 January. Global Research & Development Services, 2025. https://doi.org/10.20319/icssh.2025.1338.
Full textAbstract:
Ghana, like many other developing economies, is intricately connected to global economic trends and fluctuations. This paper investigates the influence of oil prices, exchange rate volatility and FDI inflows on Ghana’s economic growth. Moreover, it determines the level of interdependencies and the lead/lag connectedness among the variables. The study utilizes time series data from 1995 to 2022 and applies the Autoregressive Distributed Lag (ARDL) model as well as Wavelet Multiple techniques (Wavelet Multiple Correlation (WMC) and Wavelet Multiple Cross-Correlation (WMCC)). Based on the ARDL model, oil prices and exchange rate volatility adversely impact Ghana’s GDP. However, FDI inflows reveal a positive and significant relationship to GDP. Using the Wavelet model, the WMC result demonstrates stronger interdependence among the variables. Finally, the outcome from WMCC indicates that the exchange rate is the dominant variable without any lag that plays a pivotal role in determining the coherence among the economic indicators. Therefore, the study suggests that investment in renewable energy, diversification of export products and markets, enhancement of exchange rate framework, promotion of local content and linkages, and monitoring and evaluation of anti-corruption measures should be encouraged to boost the economy of Ghana.
5
Kutlutürk, Murat Mustafa, Hakan Kasım Akmaz, and Ahmet Çetin. "The Effect of Higher Education on Growth: A Cointegration Analysis." In International Conference on Eurasian Economies. Eurasian Economists Association, 2013. http://dx.doi.org/10.36880/c04.00797.
Full textAbstract:
In this study the relationship between higher education and economic growth was investigated using annual data between 1988 and 2012 for Turkey. To see short and long run effects of higher education on growth the Autoregressive Distributed Lag (ARDL) testing approach was used. In this investigation ratio of higher education graduates in employment was used as an explanatory variable. Zivot and Andrews test was implemented for the variables. The long and short run effects of higher education on growth was found significant. Granger causality test was implemented and one way Granger causality from higher education to growth was determined.
6
Szabó, Jakub, and Peter Jančovič. "Inflation Dynamics & Real Economic Activity: Examination of the Cost-Based Hybrid New Keynesian Phillips Curve for the Czech Republic." In EDAMBA 2021 : 24th International Scientific Conference for Doctoral Students and Post-Doctoral Scholars. University of Economics in Bratislava, 2022. http://dx.doi.org/10.53465/edamba.2021.9788022549301.465-475.
Full textAbstract:
The New Keynesian Phillips Curve (NKPC) became a staple in the New Keynesian economics, assuming an existence of a short-term trade-off between inflation and real economic activity, either in a form of labor unit costs or output gap. Extending the cost-based NKPC with hybrid, backward-looking price setting to the Czech Republic, we aim to examine the impact of unit labor costs, inflation expectations, import prices and real effective exchange rate on the development of inflation between 2000M1 and 2020M12. Dealing with nonstationary and cointegrated time series, we compare results employing an Error Correction Model (ECM) and an Autoregressive Distributed Lag (ARDL) model with the variables integrated in order I(1). Our data result suggest that the labor unit costs, and the inflation expectations might have an impact on the evolution of inflation based on the ECM and ARDL in differences for the Czech Republic between 2000M1 and 2020M12, although the results are too uncertain to be unambiguous.
7
Çetintaş, Hakan, and Damira Baigonushova. "Testing the Relationship Between Government Spending and Revenue: Case of Kyrgyzstan." In International Conference on Eurasian Economies. Eurasian Economists Association, 2016. http://dx.doi.org/10.36880/c07.01473.
Full textAbstract:
Sound fiscal policy is very important to promote price stability and sustainable growth in real economy. Thus, understanding the relationship between government spending and revenue is also essential to evaluate how to address fiscal imbalances. So, the focus of this research is to investigate the relationship between government revenue and spending in Kyrgyzstan. For this purpose, we have used an Autoregressive Distributed Lag (ARDL), also Variance Decomposition approach and found that these two data are cointegrated. Findings support “the tax- spend hypothesis” for fiscal discipline in Kyrgyzstan over the period of 1995-2014. In other words, according to the results, increase in real government revenue results in even higher public expenditure.
8
İsmihan, Mustafa, Mustafa Besim, and Kamil Sertoğlu. "The Impact of External Instability and Socio-economic Infrastructure on the Productivity Dynamics of North Cyprus." In International Conference on Eurasian Economies. Eurasian Economists Association, 2019. http://dx.doi.org/10.36880/c11.02350.
Full textAbstract:
This study aims to explore the long-term productivity dynamics of the economy of the Turkish Republic of Northern Cyprus by using a simple Autoregressive Distributed Lag (ARDL) Model. More specifically, we aim to analyze the impact of macroeconomic instability and socio-economic infrastructure on total factor productivity over the 1977-2017 period. Additionally, this study develops a socio-economic infrastructure index by combining information from communication, energy, education and health indicators. The main result of this paper is that while total factor productivity is positively and significantly affected by the improvements in socio-economic infrastructure it is negatively affected from the external macroeconomic instability.
9
Al-Assaf, Dr Ghazi. "Understanding the Nexus Between Oil Price Volatility and Trade Balance in GCC Countries: A Comparative Investigation of Linear and Nonlinear ARDL Models." In 5th World Conference on Business, Management, Finance, Economics, and Marketing. Eurasia Conferences, 2024. http://dx.doi.org/10.62422/978-81-968539-6-9-019.
Full textAbstract:
The GCC countries, being rich in oil deposits, have always experienced volatility in the price of oil, and the consequences are predominantly in the form of the trade balance proportions. This research work attempts to unravel the complex interplay of oil price volatility and trade balance in GCC countries through the use of comparative analysis of Linear Autoregressive Distributed Lag (ARDL) and Nonlinear ARDL models. This research uses annual time-series data covering the period 1989-2021, which includes the major GCC economies of Saudi Arabia, the United Arab Emirates, Qatar, Kuwait, Bahrain and Oman. First the research investigates the linear relationship between the volatility of oil price and trade balance that captures the traditional view of fluctuations in oil prices as a factor affecting trade balances in these countries. Then it presents an innovative method extending linear dynamics of ARDL model to complex, non-monotonic, interdependent relationships between oil price volatility and trade balance. The main results derived from both linear and non-linear ARDL estimations are presented side by side to pinpoint the underlying different mechanisms by which oil price volatility affects trade balances in GCC countries. The implementation of nonlinear dynamics will help realize the existence of components and consequences which might not be shown in the standard linear models. This comparative study not only brings the issue of the interrelatedness of oil prices and trade balances deeper into light, but also sets the tone for the application of advanced econometric techniques to account for nonlinearity and asymmetry in such relationships.
10
Đorđević, Bojan, and Sunčica Stanković. "The COVID-19 Pandemic, Government Response, and Serbian Stock Market: Evidence from ARDL Cointegration Model." In 6th International Scientific Conference – EMAN 2022 – Economics and Management: How to Cope With Disrupted Times. Association of Economists and Managers of the Balkans, Belgrade, Serbia, 2022. http://dx.doi.org/10.31410/eman.s.p.2022.59.
Full textAbstract:
The existence of a real possibility that the current health crisis could lead to an economic crisis has prompted governments worldwide to make great efforts to sustain their markets. This paper explores the impact of COVID-19 and Serbian government anti-Covid activities on the domestic stock market using the Autoregressive Distributed Lag (ARDL) Cointegration model. In its research, the paper considers the impact of the number of newly infected and the number of deaths from coronavirus daily, as well as measures taken by governments to combat viruses on the representative Belgrade stock exchange index BELEX15. The results showed a significant long-term negative impact on the number of deaths per day and international travel control on the BELEX15 index. In terms of reducing the negative consequences of the crisis caused by the global pandemic, these results could be a good guideline for effective management of government measures.
Reports on the topic "ARDL: autoregressive distributed lag"
1
Kraujalienė, Lidija, Atif Yaseen, and Inga Bilinskienė. Effects of Natural Resources and Renewable Energy Consumption on Carbon Dioxide Emmisions in the Country Economics. Vilnius Business College, 2024. https://doi.org/10.57005/ab.2024.3.5.
Full textAbstract:
Climate change is a highly debated issue among policymakers and stakeholders because it catalyzes numerous other problems. Similarly, natural resources are a blessing for any country’s economic development, but sometimes, this blessing can become a source of many problems. The research rigorously employs the Autoregressive Distributed Lag (ARDL) model, a widely accepted econometric tool for analyzing long-run relationships, and aims to investigate the impact of natural resources, renewable energy consumption, and agricultural activities on carbon emissions, considering economic growth in Russia for 30 years period. The ARDL model has evaluated that natural resources and agrarian activities significantly positively affect carbon emissions due to economic growth, while renewable energy hurts carbon emissions in Russia. This research uses a quantitative approach and relies on secondary data. Furthermore, robustness checks using Fully Modified Ordinary Least Squares (FMOLS), Dynamic Ordinary Least Squares (DOLS), and Canonical Cointegration Regression (CCR) confirmed the primary outcomes of the ARDL model. Diagnostic tests (CUSUM and CUSUMSQ) have shown the model's stability, while the multicollinearity test (VIF) has highlighted the absence of multicollinearity. The research findings have confirmed that Russia’s resources and agriculture harm the environment, while renewable energy offers a beacon of hope, promoting sustainability and economic growth. This research, with its recommendations for reducing carbon emissions in developed countries, offers a path towards a more sustainable future, inspiring optimism and hope.
2
Mehbub Anwar, Ahm, Nourah Al-Hosain, and Yagyavalk Bhatt. Analyzing the Interplay of Urbanization, Economic Development, and Seaborne Trade A Case of Saudi Arabia. King Abdullah Petroleum Studies and Research Center, 2024. https://doi.org/10.30573/ks--2024-dp62.
Full textAbstract:
Urbanization is widely recognized as a critical factor influencing economic growth and global trade, yet there is ongoing debate about whether it drives these outcomes or is a consequence of them. To address this, it is essential to determine whether urbanization spurs economic development and trade, or if these processes influence urbanization, or if the relationship is one of mutual causality. This study investigates the interplay between urbanization, economic development, and trade in both the short and the long term. Using data from Saudi Arabia spanning from 1991 to 2022, the research employs cointegration and Granger causality tests to first determine the order of integration of the variables, and it then applies the Autoregressive Distributed Lag (ARDL) model and the Error Correction Model (ECM) to examine causal relationships over different time horizons. The results reveal a bidirectional causality between urbanization and economic development in both the short and the long terms. In contrast, while there is bidirectional causality between trade and economic development in the short term, the long-term analysis indicates a unidirectional causality from trade to economic development. This suggests that trade influences economic development, which in turn affects urbanization, with no direct causality found between trade and urbanization.
3
Fossong, Derrick, and Ashu Mc Moi Ndi. Digital Tax Policy and Tax Revenue Collection in Cameroon. Institute of Development Studies, 2023. http://dx.doi.org/10.19088/ictd.2023.060.
Full textAbstract:
Cameroon adopted a digital tax policy some eight years ago. Before full implementation of the digital tax policy in 2016, councils in Cameroon, especially local councils, reported many challenges due to delays and irregularities in central government revenue-sharing (shared taxes). The direct taxes and fees collected by the councils were felt to be low, given the effort needed to collect them. It is important to understand whether adoption of the digital tax policy has increased the much-needed tax revenue for local council projects, and enhanced general tax revenue. General tax revenue refers to compulsory transfers to the central government for public purposes, and is made up of resource rent, direct and indirect taxes, and trade taxes. This study examines the impact of the digital tax policy on tax revenue collection in Cameroon using quarterly data from 2010 to 2021, employing an autoregressive distributed lag (ARDL) estimation technique. The results reveal that the digital tax policy put in place in 2016 had a positive and significant long-term impact on general tax revenue, but a negative and significant short-term impact on general tax revenue. The impact was positive but insignificant on council tax revenue in both the long and short term. Findings indicate that full positive gains from the digital tax policy in Cameroon have not yet been achieved due to local constraints in rural areas. Based on our findings, we recommend that business owners should be trained to use the online declaration and payment system. This will improve ease of use, reduce dependence on agents, and boost collection of general and council tax revenue.