Macroeconometric Model Research Articles

A Small Macro Econometrıc Model of Azerbaıjan Economy

In the presented article, the construction of the Macroeconometric model for short- and medium-term forecasting of indicators of socio-economic development in the economy of Azerbaijan has been carried out. The model consists of 64 variables (41 endogenous, 23 exogenous) and 41 equations, built in four blocks (national income account, deflators, balance of payments and public finance). The database of the model is formed in four parts, covering the years 1995-2017 on an annual basis, including national income account, deflators, balance of payments and public finance. The development of the database was carried out together with the State Statistical Committee of the Republic of Azerbaijan (SSC) in full compliance with UN standards. The methodology used includes time series stationarity tests, ARIMA models, vector error correction models and other econometric methods. As a result, a compact macroeconometric model for the economy of Azerbaijan was established. Based on the model, predictions were processed in the short-term scientific research approach and compared with the actual results.

Forecasting of changes in electricity consumption due to EV diffusion in South Korea: Development of integrated model considering diffusion and macro-econometric model

Electrification is on the increase globally. The transportation sector is being electrified to reduce greenhouse gas emissions. South Korea aims to diffuse 8.3 million battery electric vehicles (BEVs) by 2040 to reduce emissions in the transportation sector. However, BEV diffusion policies have not been considered for BEVs' electricity consumption. Given that the rapid diffusion of BEVs significantly increases the electricity demand, forecasting BEVs' electricity consumption is necessary to inform electricity production plans. Furthermore, electricity is produced through various energy sources, and electricity prices and consumption are affected; therefore, forecasts that reflect the overall energy market are needed. This study presents a forecasting model for BEV demand and energy consumption by combining it with a macroeconometric model that reflects the overall energy market and socioeconomic impact using an innovation diffusion model. Incorporating electricity prices and renewable energy consumption derived from the macroeconometric model, annual BEV demand and electricity consumption are predicted. Moreover, BEV demand is more diffused and slower when forecasted using the Generalized Bass model with electricity prices and renewable energy consumption, compared to forecast without these factors, and the predictive power of BEVs is superior to that forecasted using the Bass Model alone.

How can the preferences of policy makers be operationalised in optimum control problems with macroeconometric models? A case study for Slovenian fiscal policies

How can the preferences of policy makers be operationalised in optimum control problems with macroeconometric models? A case study for Slovenian fiscal policies

How supply and demand affect national house prices: The case of Ireland

While many western economies experienced substantial fluctuations in house prices since the turning of the century, the Irish residential market stands out as a particular case. Irish house prices experienced profound increases in the period leading up to the global financial crisis (GFC); thereafter the concomitant downturn in both the real Irish economy and financial sector precipitated a dramatic decline in prices between 2007 and 2012. However, since 2012 prices have increased in a sustained and persistent manner. A number of possible reasons are commonly cited for the recovery. In this paper we avail of a new housing and financial sector model, which are part of a broader macro-econometric model, COSMO, of the Irish economy to characterise the determinants of Irish house prices over the period 1995–2019 and in particular to examine the reasons for the post 2012 recovery. The suite of models are used to examine the contribution of developments in both monetary policy and financial stability as well as the performance of the real economy. The role played by the sluggish response of the supply-side of the Irish residential sector is also assessed. The supply-side of the Irish market was especially impacted by the GFC and has struggled to respond to the surge in housing demand which has accompanied the general economic recovery since 2012. Our results have interesting implications for the growing literature examining the intersection of monetary policy and financial stability on house prices.

Targeting Debt in Pakistan: A Structural Macro-Econometric Model

Unsustainable debt levels pose serious economic risks, potentially leading to financial instability when repayments become challenging. This paper investigates the intricate dynamics of Pakistan's debt. It aims to assess its sustainability within a broader eclectic and dynamic framework of responsible fiscal management using macro-econometric analysis. A structural macro-econometric model (MEM) based on five blocks has been developed, i.e., Government, Price, Real, Monetary, and External sectors. Moreover, it comprises sixteen behavioral equations along with ten identities. The Generalized Method of Moments (GMM) has been used to estimate the system of behavioral equations and identities to solve the endogeneity problem, while the Guass-Seidel algorithm is used for model simulation purposes, including dynamic & stochastic simulations. Forecasting has been done from 2023 – 2030. Moreover, three main policy variables, i.e., inflation, exchange rate, and government expenditures, have been given shocks to evaluate their impact on future external borrowing, interest payments along with imports, exports, and net foreign and domestic assets. The results revealed that an effective monetary & fiscal policy must be designed to stabilize the economic conditions to manage external debt and repayments effectively. Moreover, to cope with unsustainable debt conditions, it is required to follow strict fiscal discipline via designing & adhering to a budget that prioritizes inflationary controls and responsible spending practices.

NiReMS: A regional model at household level combining spatial econometrics with dynamic microsimulation

ABSTRACT The heterogeneous spatial and individual impacts of the Great Recession, Brexit and COVID-19 have generated an important challenge for macroeconomic and regional/spatial modellers to consider greater integration of their approaches. Focusing on agent heterogeneity at the ITL 1 level in the UK, we propose the National Institute Regional Modelling System (NiReMS) – a synthesis of dynamic microsimulation with a spatial regional macroeconometric model. The model gives regional macro projections while allowing for household level inference. To showcase the model, we explore the impact of discontinuing the uplift in Universal Credit (UC) before the end of the pandemic and show that it led to more households consuming less. Importantly, the proposed framework highlights the unequal distributional impact across regions of the UK.

Monetary policy implications of the new fiscal regime in Nigeria: A simulation study

In this policy research, we examine the effects of the new fiscal regime [the signing of the new Finance Act 2023, the setup of a tax reform committee, and the removal of fuel subsidy] on the Nigerian economy and its implication for fiscal and monetary policy coordination in Nigeria. We explore these by estimating a macro-econometric model, which comprises a fiscal rule, monetary policy rule, and a Phillips curve relation to simulate the impacts of the regime on fiscal, macro and monetary fundamentals in Nigeria. We find in the model estimation that (a) lower public debts can be achieved faster through a reduction in expenditure than by an increase in revenue, (b) inflation in Nigeria is driven by demand and supply-side factors, (c) the monetary policy instrument does not possess stabilizing power over the economy. The forecasting analyses show that the contractionary fiscal regime that raises the revenue by about 75 per cent will instantaneously clear out the fiscal deficit and lead to significant reductions in public debts but at the cost of higher inflation. We suggest sufficiently reducing the monetary policy rate to the optimal value obtained from the structural model, and coordination of demand management and supply-side policies by both the monetary and fiscal policy authorities in Nigeria.

Macroeconomic, energy, and emission effects of solar PV deployment at utility and distributed scales in Saudi Arabia

For the first time, this paper assesses the macroeconomic, energy, and emission impacts of solar photovoltaic (PV) deployment in Saudi Arabia by linking an energy-and-environment-sector augmented macroeconometric model with a power model and a distributed generation model while distinguishing between utility scale and distributed-generation scale of the PV deployment. We analyze three policy scenarios of deploying 5.5 TWh PV for the period 2021–2030: (S1) fully government-funded utility-scale PV deployment, (S2) half-government-funded utility-scale PV deployment, and (S3) household-funded distributed generation scale PV deployment with little government support. We find that: S1 is best suited if the objective is fiscal expansion, 2 is best suited to improve non-oil fiscal positions, increase non-oil value added and employment, and increase household consumption, and S3 is best suited to reduce energy consumption and associated emissions and enhance international trade. We show that government and foreign investment play an important role, and it would be desirable for the Saudi government to partner in financing renewable energy projects, saving budgetary resources to invest in other projects to support economic growth.

Financial frictions in a macroeconometric model: A counterfactual analysis for the case of Slovenia

The paper investigates the importance of modelling the effects of financial frictions in a macroeconometric framework for the small open economy of Slovenia. We enhance the model with additional behavioural equations pertaining to business and residential investment, the respective lending rates, and the gross operating surplus of non-financial companies. The estimation period spans from 1999Q1 to 2019Q4, meaning a period of significant financial distress was included in the analysis. Counterfactual analysis was conducted by comparing simulation results from a macroeconometric model with the explicit modelling of financial frictions to a model with limited transmission effects. The results indicate that financial frictions significantly hinder macroeconomic development under adverse macroeconomic scenarios. Policymakers’ measures should focus on maintaining financial sector stability and enabling external financing access for non-financial companies and households during adverse economic situations.

Macroeconomic Impacts of Immigration in the Canadian Atlantic Region: An Empirical Analysis Using the FOCUS Model

We simulate the impact of an increase in immigration into the Atlantic Provinces based on the FOCUS macro-econometric model at the University of Toronto. That national model was adapted to reflect the regional dimensions of the Atlantic Provinces. We find robust evidence of positive outcomes for the Atlantic region so long as it is part of a broader increase in immigration for the country as a whole. The positive outcome encompasses higher GDP and GDP per capita, higher consumption, and improved government fiscal balances at both the federal and provincial levels that could in turn be used for tax reductions or the enhancement of government services. These benefits could be enhanced further by carefully targeting new immigrants for needed skills and for their likelihood of remaining in the Atlantic region.

A New Look at Cross-Country Aggregation in the Global VAR Approach: Theory and Monte Carlo Simulation

AbstractRequirements to understand and forecast the behavior of complex macroeconomic interactions mandate the use of high-dimensional macroeconometric models. The Global Vector Autoregressive (GVAR) modeling technique is very popular among them and it allows researchers and policymakers to take into account both the complex interdependencies that exist between various economic entities and the global economy through the world’s trade and financial channels. However, determining the cross-section unit size while using this approach is not a trivial task. In order to address this issue, we suggest an objective procedure for the detection of the size of the cross-country aggregation in GVAR models. While doing so, we depart from the Akaike Information Criterion (AIC) and propose an analytical modification to it, mainly employing an ad hoc approach without violating Akaike’s main principles. To supplement the theoretical results, small sample performances of those procedures are studied in Monte Carlo experiments as well as implementing our approach on real data. The numerical results suggest that our ad hoc modification of AIC can be used to determine the structure of the cross-section unit dimension in GVAR models, allowing the researchers and policymakers to build parsimonious models.

A micro-macro approach for the evaluation of fiscal policies: The case of the Italian tax-benefit reform

A comprehensive evaluation of fiscal policy reforms requires a methodology that simultaneously considers their aggregate impact on the economy as a whole as well as their distributional implications at the individual or household level.In this paper, we provide a new link between a fiscal microsimulation model and a macro-econometric model and we analyze the impact of the reform of the Italian tax-benefit system occurred in 2022.The reform is expected to have a first-round cost of about 15 billion euros due to the tax cut and the increase in child related benefits, with a reduction in inequality of around 0.5 percentage points of Gini index. The second-round effects confirm the reduction in inequality and indicate an initial self-financing effect of about 7%. Our estimates support the importance of integrating micro- and macroeconomic insights for a more accurate assessment of the impact of public policies.

Examining Trade-Growth Relationships in RCEP through Small Macroeconometric Models

Examining Trade-Growth Relationships in RCEP through Small Macroeconometric Models

A Small Macroeconometric Model of the Philippine Economy

A Small Macroeconometric Model of the Philippine Economy

ECB Macroeconometric Models for Forecasting and Policy Analysis

ECB Macroeconometric Models for Forecasting and Policy Analysis

The impact of climate change mitigation policies on European labour markets

We study the impact of climate change mitigation policies intended to reach the Paris Agreement’s two-degree target on the structure of European labour markets. Employing a three-sector macro-econometric model with a rich labour market extension, we show that the measures targeted at shrinking the use of fossil fuels in electricity generation and the road transport sector – both of which have an overall modest, positive impact on GDP and total employment – could make occupational structure less unequal and polarised in 2030, the target deadline. This could occur in more than half of the European Union’s member states, particularly where the industries most affected by the transition to a low-carbon economy (i.e., mining and quarrying, utilities and manufacturing of coke and refined petroleum products) remain most important.

Dealing with the COVID-19 pandemic in Slovenia: simulations with a macroeconometric model

In this paper we analyse the effectiveness of fiscal policies with respect to macroeconomic stabilisation during the COVID-19 pandemic in the small open economy of Slovenia. Using SLOPOL11, an econometric model of the Slovenian economy, we simulate the development of the its economy during the 2020s under alternative assumptions about future pandemic-related shocks. We also determine optimal fiscal policies to combat the effects of the pandemic and to stabilise the economy under two scenarios for the future course of developments under COVID-19. Our simulations show that those public spending measures that entail both demand- and supply-side effects are more effective at stimulating real GDP and increasing employment than pure demand-side measures. Successful stabilisation policies should thus contain a supply-side component in addition to a demand-side component.

How do system-wide net-zero scenarios compare to sector model pathways for the EU? A novel approach based on benchmark indicators and index decomposition analyses

The use of scenarios and quantitative modelling to identify pathways for energy system transformations in line with the Paris targets is well established in the field of energy and climate policy. The resulting decarbonization pathways depend on both assumptions and the type of model used (e.g., integrated assessment models, energy system, macro-econometric or bottom-up sector models). The objective of this article is to analyze how energy demand sectors in system-wide net-zero scenarios for the EU compare to the results of sector-specific models. To this end, a novel approach referred to as “sectoral benchmarking” is developed and applied, combining the application of standard indicators such as energy intensity, electrification rate or carbon intensity with an index decomposition analysis. The combined approach allows visualizing how system-wide decarbonization pathways differ from the sector models' pathways by bringing the model output in a harmonized format for an efficient comparison. The analysis compares pathways from four different modelling tools: two European system models, one of which is an energy system model (EU TIMES) and the other a macro-econometric model (NEMESIS); as well as two sector-specific models, for transport (ALADIN) and for the industry and building sectors (FORECAST). We evaluate the system model's net-zero scenarios by comparing them to a corridor given by the sector models' current policy and net-zero emission scenarios. This corridor represents what the sector models deem as plausible from their bottom-up perspective within the boundaries of current policies and ambitions to reach net-zero.Our results show that the system model net-zero pathways differ substantially from the sectoral perspective in all sectors. In the industry and building sectors, both system models' decarbonization ambitions are within the sector corridor, but the employed mitigation levers differ. In the industry sectors, the sectoral model achieves substantial CO2 emission reductions with electrification, while the system models use more bioenergy (EU TIMES) or more energy efficiency (NEMESIS). In the building sector, both system models rely mostly on electrification, while the sector models relies on biomass and some district heat and electrification. In the transport sector, both system models' decarbonization ambition is substantially lower than the sector model's.The observed differences are caused by a variety of factors, which we evaluate in this article. One reason is the system models' lower ambition to decarbonize the end-use sectors due to their ability to compensate with negative emission technologies across sectors. In addition, employed mitigation levers differ due to the models' differing capabilities to consider technologies as well as differences in the allocation of bioenergy to sectors.Our findings can be used to determine how the different types of models can inform each other and to make the diverging decarbonization pathways more transparent to policy-makers and other relevant stakeholders.

Impact of Carbon Neutrality on the Economy and Industry Assuming Japan’s Achievement of 2030 Power Mix Plan: A 2050 Perspective Based on the E3ME Macro-Econometric Model

Impact of Carbon Neutrality on the Economy and Industry Assuming Japan’s Achievement of 2030 Power Mix Plan: A 2050 Perspective Based on the E3ME Macro-Econometric Model

Forecast accuracy of the linear and nonlinear autoregressive models in macroeconomic modeling

AbstractMost nonlinear vector autoregressive methods in the econometric literature are based on specific functional forms, such as the smooth transition autoregressive model. This study proposes a general form of the nonlinear vector autoregressive model based on global approximators, such as neural networks, Volterra, and Weiner series. The simulation results of 20 linear and nonlinear multivariate time series processes indicate that nonlinear vector autoregressive methods, especially multi‐output neural networks, are more accurate based on the root mean square error and model confidence set criteria. Applying the global approximator approach to a small‐scale macroeconometric model reveals that the new approach can improve forecast accuracy compared to linear and other nonlinear vector error correction models. In addition, forecasting the relevant variables in a typical exchange rate and monetary policy models based on nonlinear specifications gives more successful results than in the linear case.