A Review of Macroeconometric Modeling Practices

Akbar, Muhammad; Ahmad, Eatzaz

doi:10.32368/fjes.20141002

Cited by 4 publications

(3 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…A significant amount of literature is available in the context of macroeconometric modeling [9][10][11]. Akbar and Ahmad [12] present a good review and critique of macroeconometric modeling practices. Acosta et al [13] discussed two projects undertaken by the Social Science Research Council on constructing a macroeconometric model (1960)(1961)(1962)(1963) and the organization of its conference on quantitative policy analysis in 1963.…”

Section: Review Of the Literaturementioning

confidence: 99%

Import Tariff Reduction and Fiscal Sustainability: A Macro-Econometric Modelling for Ethiopia

Ramakrishna¹,

Gizaw

Paramaiah

et al. 2023

Sustainability

View full text Add to dashboard Cite

The main objective of this study is to examine the dynamic impact of import tariff reduction on major macroeconomic variables and its long-run implications for the fiscal sustainability of Ethiopia. In addition, it estimates the increase in the average consumption tax required to compensate for the possible tax revenue loss and fiscal sustainability. A Recursive Dynamic Computable General Equilibrium Model (RDCGEM) is used to assess the dynamic impact on macroeconomic variables of import tariff reduction and examine the increased consumption tax required. The study is novel as there are no studies in general, and for Ethiopia in particular in this regard. We use the available 2013/2014 base year macroeconomic data from national income accounts, fiscal accounts, and balance of payments accounts of Ethiopia. The RDCGEM is calibrated to the base year data, checked for correctness, and tested for robustness using sensitivity analysis. The model then is simulated for the import tariff reduction under the base case and under various tariff reduction scenarios based on which the macroeconomic impacts of tariff reduction are analyzed. Based on the RDCGM outputs, the fiscal sustainability impact of import tariff reduction is verified, and using a cointegration method, we examine the sustainability of fiscal policy. The results suggest a 95 percent import tariff reduction that negatively impacts the major macroeconomic variables. It also leads to long-term fiscal unsustainability. The joint reform of the country has relatively better impacts on major macroeconomic variables but slightly negative effects on household income and consumption.

show abstract

Section: Review Of the Literaturementioning

confidence: 99%

Import Tariff Reduction and Fiscal Sustainability: A Macro-Econometric Modelling for Ethiopia

Ramakrishna¹,

Gizaw

Paramaiah

et al. 2023

Sustainability

View full text Add to dashboard Cite

show abstract

“…These models are used to identify the function of the national economies. It provides a common framework to make ex-ante forecasts under alternative experiments, to evaluate policies, and scenarios and for communication (Akbar and Ahmad, 2014). Granger (1999) argues that since economic theories are necessarily simplifying abstractions, translation of theoretical to econometric models must lead to problems like biased coefficient estimates, wrong signs of coefficients, and residual properties that hamper valid inference.…”

Section: Inflation and Economic Growthmentioning

confidence: 99%

Factors Influencing Inflation and Economic Growth in Pakistan: An Econometric Analysis

Azra¹,

Afzal²,

Khan³

2020

SJA

View full text Add to dashboard Cite

It is the need of the hour that in the wake of global dynamics, macro-economy of Pakistan is examined in detail. This may enable the policy makers to rethink and recast the growth and development objectives and strategy. Economic growth depends on a large number of social, economic, political, demographic, financial and global factors.Macroeconomics is based on General Equilibrium approach implying that the economy is influenced by the interplay of all conceivable factors. It is extremely Abstract | This paper made an econometric investigation of inflation and economic growth in Pakistan for the period 1990-2017. Money supply, imports, exchange rate and budget deficit were the major causes of inflation. Growth in GDP is expected to lead to a reduction in inflation. To combat inflation, unwarranted growth of money supply is checked and the exchange is stabilized. It is less likely that imports are reduced to lessen inflation due to economy needs. It appears difficult that GOP succeeds in curtailing the BD because of the widespread corruption and money-laundering. Human resource development coupled with investment and value-added by both agriculture and industry contributed significantly to economic growth. Should the policy makers attach genuine attention to these factors, it is expected that Pakistan economy will perform reasonably well. Specification and diagnostic tests revealed the appropriateness and soundness of the inflation and economic growth models. Parameters stability was examined for two periods (1991 and 2002). CPI showed stability in both periods but GDP did not demonstrate in the second period.

show abstract

“…Econometric models are simulation models, which are based on the theoretical ideas of economic modelling structural constraints and their behaviour when the equilibrium state changes [7]. The problem lies in the interpretation of the results rendered by the model.…”

Section: Introductionmentioning

confidence: 99%

A Review on Classification of the Urban Poverty Using the Artificial Intelligence Method

Zakaria

Hassan

Othman

et al. 2017

Journal of Asian Scientific Research

View full text Add to dashboard Cite

Article History Keywords Urban poverty Artificial intelligencePoverty and how it has been assessed and measured is a frequently discussed topic by policy makers and social developers. The identification process in poverty measurement is indeed essential towards acknowledging the poor in the population; hence this needs to be clarified. Malaysia measures poverty by means of poverty line, indicating the unidimensional and inflexible distribution of poor and non-poor especially in urban areas. Many researchers have used fuzzy logic to solve the problem of rigid poor/nonpoor dichotomy. This current trend has been able to augment the gap between the rigid and inflexible classification of poor and non-poor. However, there are still several shortcomings that need attention. For instance, the classification of the poor in fuzzy logic that is based on the average income of households still does not cover on the different range of disadvantage on non-monetary items. Based on these trends, ANFIS is proposed to resolve on the highlighted issues. The winning features of ANFIS, which include on simplicity in implementation, understandable explanation facilities through fuzzy rules, and ease of incorporation of both linguistic and numeric knowledge for problem solving may help in producing better result in classification of the urban poor. Essentially, the neural network is proposed to complement the fuzzy system, hence overcoming the limitations of both fuzzy systems and neural networks. As such, ANFIS method is used in this study to better classify on the poor and non-poor compared to fuzzy rule-based system which is lacking in prediction error rate due to too many variables used. However, this method deteriorates from misclassified poverty indicators; hence this study proposed on ensemble ANFIS to produce more accurate and robust classification results. An ensemble model is usually employed to address the problems of over-fitting, high dimensionality or missing features in the training data. Generally, combining multiple classification models increases predictive performance compared to the use of an individual model alone. Therefore, based on these current trends, this study is aimed to do a review on classification of the urban poverty using the artificial intelligence method.Contribution/ Originality: This study contributes in the existing literature of state-of-the-art urban poverty classification methods from the perspective of the modern Artificial Intelligence approach, which is compared with the conservative econometric model. In addition, the implementation of ANFIS and classification ensemble learning in urban poverty classification are also briefly discussed.

show abstract

A Review of Macroeconometric Modeling Practices

Cited by 4 publications

References 23 publications

Import Tariff Reduction and Fiscal Sustainability: A Macro-Econometric Modelling for Ethiopia

Import Tariff Reduction and Fiscal Sustainability: A Macro-Econometric Modelling for Ethiopia

Factors Influencing Inflation and Economic Growth in Pakistan: An Econometric Analysis

A Review on Classification of the Urban Poverty Using the Artificial Intelligence Method

Contact Info

Product

Resources

About