Aggregate Demand Model Research Articles

Élasticités et effet rebond des véhicules légers au Canada

Although reducing greenhouse gas emissions is an imperative, environmental policies can run into two pitfalls: the rebound effect and inelastic demand for gasoline. If a vehicle is more fuel-efficient but is used more often, this reduces the expected energy savings (rebound effect). Similarly, increasing the price of gasoline via carbon pricing has little effect on demand if it is not very sensitive (inelastic) to price. To determine the value of these parameters for light vehicles in Canada, I use data for the ten provinces between 2000 and 2019 to estimate a simultaneous three-equation model of aggregate demand for kilometers traveled, vehicle fleet and fuel efficiency. While the rebound effect is worth 9 % in the short term and 30 % in the long term, gasoline demand is found to be inelastic in both cases. These values are broadly consistent with those found in the literature. A rise in gasoline prices therefore reduces purchasing power rather than consumption. Similarly, in the long term, a 10 % increase in fuel efficiency would increase distance travelled by 3 %.

Multi-period urban hydrogen refueling stations site selection and capacity planning with many-objective optimization for hydrogen supply chain

The location and quantity of hydrogen refueling stations (HRSs) play a crucial role in the development and promotion of hydrogen fuel cell vehicles (HFCVs). This study proposes a multi-period urban HRSs site selection and capacity planning with many-objective optimization framework for hydrogen supply chain (HSC). Firstly, the city's multi-period hydrogen requirement is predicted based on a generalized Bass diffusion model. Using publicly available data, including gas station network data, geographic information system (GIS) data, population data, and regional economic data, a spatially aggregated demand model is established to allocate hydrogen requirement at candidate sites in the city of the geographic grid model with a 1 km resolution. On this basis, four interrelated objective functions (total investment cost, hydrogen requirement coverage, risk coefficient, and environmental factors) are developed. The third-generation non-dominated sorting genetic algorithm (NSGA-III) and the technique for order preference by similarity to an ideal solution (TOPSIS) are employed to achieve multi-period urban HRSs site selection and capacity planning with many-objective optimization for HSC. By comparing the results of single-objective optimization focusing on minimum cost and maximum hydrogen requirement coverage, it is observed that many-objective optimization achieves a better balance among the four conflicting objectives. After comprehensive analysis, the distribution of HRSs exhibits a clustered structure, influenced by the population and economic structure of the city. In the initial stages of HFCV development, most stations serve the peripheral areas around the city center; while n the later stages of the optimization period, a few high-capacity HRSs begin to concentrate in the city center.

Applying the AD-AS Model to the Housing Market of Post-Socialist Economies

We propose applying the standard aggregate demand and aggregate supply model (AD-AS) to the housing market. It is a very simple and intuitive tool that can help shed light on the major forces at play in the market and that can supplement the use of the general equilibrium and dynamic stochastic equilibrium models (DSGE). The latter models are very sophisticated and aim to cover many aspects of the economy, but they require a significant number of long time series to estimate the model parameters. However, in many countries, such as post-socialist countries, the time series are short. Those models moreover cover only real house prices, but in certain situations we should consider real and nominal prices at the same time.

Nonparametric identification of random coefficients in aggregate demand models for differentiated products

Summary This paper studies nonparametric identification in market-level demand models for differentiated products with heterogeneous consumers. We consider a general class of models that allows for the individual-specific coefficients to vary continuously across the population and give conditions under which the density of these coefficients, and hence also functionals such as the fractions of individuals who benefit from a counterfactual intervention, is identified.

Keynesian approach to economy regulation: answers to the challenges facing the agro-industrial complex

The paper presents the main aspects of the Keynesian theory of state economic policy in the context of responding to global challenges and national barriers facing the development of the Russian agro-industrial complex. The purpose of the work is to explore the possibilities of the Keynesian approach to respond to the challenges facing the agro-industrial complex of modern Russia. The methodological basis of the study is an integrated approach. The study identifies the main postulates of Keynesian theory. On the basis of macroeconomic models of aggregate demand and aggregate supply, the Keynesian cross, the features of the Keynesian approach to the regulation of economic activity in terms of investment, savings, and consumption are formulated. The Keynesian macroeconomic model of state policy is presented, implemented by increasing the real volume of investment expenditures through fiscal and monetary policies; methods of increasing effective solvent demand; reducing the fiscal burden on the population and business. The limits of the application of Keynesian methods are defined: "liquidity trap”; the emergence of a chronic budget deficit; the attenuation of the multiplier-acceleration mechanism; “stagflation”; “inflationary spiral”. The relevance of the application of Keynesian methods of regulation in the modern Russian agro-industrial complex is substantiated: fiscal methods can have a beneficial effect on the development of agriculture: the growth of investments in the agricultural sector by 1%, stimulates economic growth in the industry by 0.64%; monetary methods have a long-term significant impact on the agricultural sector development; an increase in effective solvent demand for food in conditions of insufficient demand for food products in Russia is of high importance; a reduction in the fiscal burden can have a beneficial impact on agriculture development.

How Do Different Brand Equity Measures Affect Long-Term Promotional Effectiveness?

Abstract Studies on the relationship between brand equity and long-term promotional effectiveness have many issues. Brand equity measures can be classified as either consumer-based (CB) or firm-based (FB) measures. Previous literature has mostly focused on one or the other type of measure, mostly due to computational difficulties or data limitations, making it difficult to determine whether the results can be generalized to all types of measure. In addition, long-term promotional effectiveness remains a debatable issue due to complicated long-term effects. Our study is the first to include both CB and FB brand equity measures in a long-term promotional effectiveness study. Using weekly scanner data in the breakfast category covering a three-year period, we are able to compute a variety of popular operationalizations of brand equity measures by employing the aggregate demand model and capture total long-term effects via the persistence model. Our major finding is that the general consensus that higher brand equity generates higher promotional effectiveness applies only to typical FB measures—not CB measures. Moreover, we show a positive accumulated long-term effectiveness and an absence of permanent effects for all our brands. These results offer new insights into the differentiation of major brand equity measures and long-term promotional effectiveness.

Alleviating demand uncertainty for seasonal goods: An analysis of attribute-based markdown policy for fashion retailers

This study develops a model for pricing seasonal goods, helping retailers better cope with demand uncertainty. Specifically, to improve price markdown policies for fashion apparel retailers, we uncover the relationship between fashion product characteristics and consumers’ within-season product adoption behavior. We develop an aggregate demand model and estimate it using a finite mixture model on data from a leading specialty apparel retailer. The demand model identifies two latent classes of products based on the evolution of demand within a product’s lifecycle (i.e., sharply deteriorating vs. stable demand), and accounts for unobserved heterogeneity where mixing probabilities are defined as functions of fashion product attributes. We then run hundreds of counterfactuals to evaluate pricing policies in terms of: (1) timing and (2) depth of price markdowns. Our findings show that the retailer should implement middle-of-the-season price markdowns for products that have high initial prices, are introduced in the summer/fall, or are darker in colors. For other products, markdowns should be shallower and earlier in the season. We show that ignoring the cross-product heterogeneity in within-season demand could result in a 5.77% reduction in revenues. Our solutions provide managerial implications and enable the retailer to predict products’ demand patterns prior to launching products in the market.

Is growth in the South African economy profit-led or wage-led?

Orientation: This article assessed the impact of functional income distribution on economic growth, and how it can characterise the growth regime as profit-led or wage-led.Research purpose: This study investigated whether the problem of falling wage share as a percentage of gross domestic product (GDP) may have characterised growth as wage-led or profit-led between 1975 and 2019 in South Africa.Motivation for the study: Economic growth in South Africa has been low post the 2008 financial crisis and employees complain about insufficient wages.Research design/approach and method: This article used the Keynesian aggregate demand model and conducted an autoregressive distributed lag (ARDL) approach to assess the presence of a long-run relationship between changes in income distribution and aggregate demand.Main findings: The study found that the profit rate, rate of capacity utilisation and the real exchange rate have an influence on net exports. Profit rate and rate of capacity utilisation influenced aggregate consumption. Investment was affected by business confidence, profit rate, foreign demand and rate of capacity utilisation. Demand formation was exhilarationist and growth was profit-led. The foreign sector amplified the extent of profit-ledness.Practical/managerial implications: Government should create policies to reduce inequality in income shares. Institutions should consider reformulating labour dynamics to manage the extent to which the foreign sector amplified the economy to be profit-led.Contribution/value add: The South African economy is profit-led, inconsistent with developed country literature, which suggests that economies are generally wage-led. The findings highlight the importance of the foreign sector in determining the demand formation and growth regimes in the economy.

Examining the determinants of import demand in Tanzania: An ARDL approach

Objective: This study estimates the determinants of import demand in Tanzania using time-series data for the period from 1985 to 2015. Research Design & Methods: The study applied the ARDL approach on Tanzania’s time-series data to examine the key drivers of import demand. The study used both aggregate import demand model (i.e., Model 1) and disaggregated import demand models, i.e., Model 2 (for consumer goods), Model 3 (for intermediate goods) and Model 4 (for capital goods) to examine this linkage. Findings: The study found that in Model 1, aggregate imports in Tanzania are positively influenced by investment and exports, and negatively determined by trade policy. In Model 2, it was found that imports for consumer goods are positively influenced by consumer spending and foreign reserves, but negatively influenced by trade policy. In Model 3, imports for intermediate goods were found to be positively influenced by exports in the long run. Finally, in Model 4, the study found imports for capital goods to be positively influenced by exports (in the short- and long-run), but negatively influenced by investment (in the short-run). Implications & Recommendations: The study recommends that policymakers in Tanzania should strengthen their macroeconomic policies to ensure that their imports are not consumption-based and have an enhancing effect on the country’s economic activities. Contribution & Value Added: The study contributes to the empirical body of knowledge by incorporating various components of disaggregated import demand. This is an aspect that is scant in the existing literature as most previous studies only focused on aggregate import demand.

A Simulation-Based Heuristic to Find Approximate Equilibria with Disaggregate Demand Models

Oligopolistic competition occurs in various transportation markets. In this paper, we introduce a framework to find approximate equilibrium solutions of oligopolistic markets in which demand is modeled at the disaggregate level using discrete choice models, according to random utility theory. Compared with aggregate demand models, the added value of discrete choice models is the possibility to account for more complex and precise representations of individual behaviors. Because of the form of the resulting demand functions, there is no guarantee that an equilibrium solution for the given market exists, nor is it possible to rely on derivative-based methods to find one. Therefore, we propose a model-based algorithmic approach to find approximate equilibria, which is structured as follows. A heuristic reduction of the search space is initially performed. Then, a subgame equilibrium problem is solved using a mixed integer optimization model inspired by the fixed-point iteration algorithm. The optimal solution of the subgame is compared against the best responses of all suppliers over the strategy sets of the original game. Best response strategies are added to the restricted problem until all ε-equilibrium conditions are satisfied simultaneously. Numerical experiments show that our methodology can approximate the results of an exact method that finds a pure equilibrium in the case of a multinomial logit model of demand with a single-product offer and homogeneous demand. Furthermore, it succeeds at finding approximate equilibria for two transportation case studies featuring more complex discrete choice models, heterogeneous demand, a multiproduct offer by suppliers, and price differentiation for which no analytical approach exists.

Effects of built environment and weather on demands for transportation network company trips

This paper investigates the effects of the built environment and weather on the demands for transportation network companies (TNC) in Toronto. The research is based on a historical dataset of Uber trips from September 2016 to September 2018 in Toronto. A wide range of built environments, sociodemographic, and weather data are generated at the dissemination area-level and fused with the monthly aggregated Uber dataset. To provide insight into the underlying factors that affect TNC demand, a series of aggregate demand models are estimated using log-transformed constant elasticity demand functions, with consideration of the seasonal lag effect. To capture the weather effect, an autoregressive moving average model is estimated for the downtown core of Toronto. The model results show that the influence of lagged ridership and seasonal lag effect have a positive correlation with TNC demand. The trip generation and attraction models reveal that TNC trips increase where when the commuting trip duration is longer than 60 min. It is found that the number of apartments in a dissemination area is positively correlated with TNC trip generation, while the number of single-detached houses has a negative correlation. The time-series model indicates that temperature and total daily precipitations are positively correlated with TNC demand. Due to the lack of comprehensive data sources on the Uber and Lyft ridership, the policymakers often struggle to make evidence-based policy recommendations to regulate such disruptive technologies. The series of models presented in this study will help us better understand the potential users of transportation network companies (TNC) and the effects of land use, built environment and weather on transportation network company trips.

Modeling the impacts of electric bicycle purchase incentive program designs

ABSTRACT Governments are interested in incentivizing e-bike adoption, due to potential benefits from displacing travel by private automobile. To inform the development of e-bike purchase incentive programs, the objective of this paper is to determine how key elements of program design (particularly rebate amounts and structure) are expected to affect new e-bike purchases. An aggregate demand model is developed and applied to rebate scenarios to examine incentive effectiveness. Results show that rebate programs are expected to be bound by available rebates, not e-bike demand, and additional bike shop revenues exceed rebate costs. At a fixed program budget, fewer, larger rebates yield fewer additional sales, but a larger share of rebates go to low-income and new (marginal) purchasers. Flat and proportional rebate structures yield similar sales, although flat rebates are more income-equitable. Flat rebates are recommended for new e-bike incentive programs, with robust program evaluations to inform future program designs.

قياس مصادر التضخم في الاقتصاد العراقي باستخدام أنموذج الإنحدار الذاتي للفجوات الزمنية الموزعة المتباطئة (ARDL) للمدة (1970-2018)

Inflation posed a challenge to the Iraqi economy and its effects on economic activity and growth rates. This study investigates the sources of inflation in the Iraqi economy during the period (1970-2018) within the framework of the aggregate supply and aggregate demand model using the Self-Regression of Slow Distributed Gaps (ARDL) model. The results of the study showed that the inflation rate in Iraq is affected by the following variables: (money supply, parallel market exchange rate, consumer spending, the oil sector’s contribution to GDP and the degree of economic openness) and all are related to an inverse relationship with the rate of inflation except for money supply and consumer spending, as It has a direct relationship with it, and there is a long-term equilibrium relationship (co-integration) between the studied variables according to the Bound Test methodology. Through the value of the error correction vector coefficient (1.35%) of the short-term errors are automatically corrected during the unit time (year) to reach the equilibrium in the long term.

An investigation into changes in the elasticity of U.S. residential natural gas consumption: A time-varying approach

This study examines whether the responsiveness of U.S. residential natural gas demand to price and income movements has changed in recent times. Using annual data from 1970 to 2016, we apply a conventional aggregate demand model to estimate the own price and income elasticity of natural gas consumption by residential users in the U.S. We estimate this as a static model across alternative sample periods, as well as a stochastic model over the full sample, and reach two main conclusions. First, the own price elasticity of natural gas demand increased sharply in the mid 1980's and has declined steadily since. This finding is consistent with increasing reliance on natural gas by residential consumers and improvements in energy efficiency. Second, the income elasticity of U.S. residential natural gas demand has remained relatively constant and consistently negative. We explain this result by reference to increasing energy efficiency as well as the Environmental Kuznets Curve. The findings have important implications regarding the effectiveness of price and income measures to influence energy consumption and the energy mix.

Beyond Keynes and the Classics. Outline of the Goods Side/Money Side Model of the Business Cycle and Macroeconomic Configurations

This paper presents the goods side/money side (GSMS) model as a novel way of macroeconomic analysis. The GSMS model goes beyond Keynesianism as it makes a sharp distinction between the goods side and the money side and thus avoids the indistinctness between real nominal values that come with spending in aggregate demand models. The GSMS model transcends classical macroeconomics in its traditional and modern versions as it reinstates money as an active factor in the economy. Different from monetarism, the key monetary concept of the GSMS model is «macroeconomic liquidity», which includes velocity of circulation. The present paper presents the basic features of the model and shows its use by analyzing macroeconomic configurations, the business cycle, and economic growth. The paper includes an appendix with an evaluation of macroeconomic configurations in the light of the GSMS model.
 Key words: GSMS Macroeconomic Model, Monetary Policy, Economic Growth, Austrian Theory of the Business Cycle (ATB).
 JEL Classification: A23, E32, E52.
 Resumen: Este trabajo presenta el modelo lado del mercado de bienes/lado del mercado de dinero (GSMS) como una nueva forma de análisis macro-económico. El modelo GSMS va más allá del keynesianismo, ya que hace una clara distinción entre el lado de los bienes y el lado del dinero y, por tanto, evita la ausencia de diferenciación entre los valores nominales y reales que vienen con el gasto en los modelos de demanda agregada. El modelo GSMS trasciende la macroeconomía clásica en sus versiones tradicional y moderna, ya que restituye al dinero un rol activo en la economía. A diferen-cia del monetarismo, el concepto monetario clave del modelo GSMS es la «liquidez macroeconómica», que incluye la velocidad de circulación. El pre-sente artículo presenta las características básicas del modelo y muestra su uso mediante el análisis de configuraciones macroeconómicas, el ciclo eco-nómico y el crecimiento económico. El documento incluye un apéndice con una evaluación de configuraciones macroeconómicas a la luz del modelo GSMS.
 Palabras clave: Modelo Macroeconómico GSMS, Política Monetaria, Cre - cimiento Económico, Teoría Austriaca del Ciclo Económico.
 Clasificación JEL: A23, E32, E52.

A Keynesian model of aggregate demand in the long‐run

AbstractThis paper develops the Keynesian theory of aggregate demand in the long‐run in which persistently low levels of aggregate demand can generate persistently low levels of activity with the associated persistently high rates of unemployment. Wages are determined by firm‐worker bargaining/sharing. Investment is influenced by monopoly power, aggregate demand and the interest rate. Decreasing rates of deflation of money wages and prices even at high rates of unemployment are prevented by workers being assumed to be loss averse with respect to reductions in their wages below a reference real wage.

Understanding Coronanomics: The Economic Implications of the Covid-19 Pandemic

The globalization of the COVID-19 pandemic and its economic impacts is set to run havoc across economies in the world, throwing many into recession and possibly depression. The aim of this paper is to provide an overall understanding of the likely macroeconomic shocks of the pandemic on a diverse range of economic activities and indicators across economies. The paper covers implications to demand, supply, supply chain, trade, investment, price level, exchange rates, and financial stability and risk, growth, and international cooperation. The paper combines a unique theoretical impact mapping and supplements it with emerging evidence to develop the impacts' likely progression and span. Furthermore, the paper uses a standard Aggregate Demand and Aggregate Supply (AD-AS) model of macroeconomics to explain the likely growth effects arising out of essential and non-essential goods markets and outlines necessary features policy responses should consider. Data and information to analyze the impacts are assimilated from different sources, including news and media publications, the OECD, and IHS Markit-CIPS. Assessments of this paper suggest that many economies are about to see a period of stagflation driven by demand and supply slump, increased unemployment, deflationary pressure, reduced trade flows, and disruptions in the supply chain, which may result in a recessionary period if not acted fast with innovative policy responses. As almost all economies are badly affected, a global growth recession is imminent if the pandemic continues. However, based on past experience of pandemics and epidemics and the current evidence, a U-shaped recovery pattern is the most optimistic possibility for most countries and the world economy. The paper could help policy-makers in understanding the pandemic's broad-based impacts and policy needs to fight the imminent economic damage. Particularly, assessments with respect to the essential and non-essential goods markets could provide useful insights in designing appropriate policy responses to fight the pandemic. All considered, the paper calls for a collective and globalized response alongside standalone policy responses undertaken by individual economies. The assessments are broadly in line with the limited literature available on macroeconomic implications of CVODI-19 and could serve as a basis for advanced analysis on COVID-19 economics.

The Economic Consequences of the COVID-19 Pandemic in Nigeria

The Covid-19 pandemic has generated shocks that have caused economic fluctuations globally, calling for an understanding of the behaviour of macroeconomic variables. This study presents an early review of the macroeconomic impact of the Covid-19 pandemic in Nigeria. The aggregate supply and aggregate demand (AS-AD) model provides the theoretical motivation for the study. From the findings, while the number of infected cases reflects significant correlations with economic activity from the perspective of a trend analysis, the estimates from dynamic ordinary least squares (DOLS) show that nexuses between the number of confirmed cases and attendant macroeconomic outcomes are largely insignificant with the expected signs. The study has therefore shown that the Covid-19 pandemic has insignificant negative impacts on basic macroeconomic variables in Nigeria such as inflation, employment, exchange rate, GDP growth, among others. In other words, time is required before the established correlations withstand empirical scrutiny in terms of causality. As the government has engaged the Economic Sustainable Plan (ESP, 2020), which is a post-Covid-19 recovery plan, it is hoped that the attendant policies would be properly implemented so as to provide the critical mass to repositioning the country’s economy on the path towards inclusive and sustained economic development.

The Effect of Consideration Set on Market Structure

We estimate a choice-based aggregate demand model accounting for consumers" consideration sets, and study its implications on market structure. In contrast to past research, we model and estimate consumer demand using aggregate-level consumer browsing data in addition to aggregatelevel choice data. The use of consumer browsing data allows us to study consumer demand in a realistic setting in which consumers choose from a subset of products. We calibrate the proposed model on both data sets, avoid biases in parameter estimates, and compute the price elasticity measures. As an empirical application, we estimate consumer demand in the camcorder category and study its implications on market structure. The proposed model predicts a limited consumer price response and offers a more discriminating competitive landscape from the one assuming universal consideration set.

A macroeconomic simulation for Greece in the wake of its government debt crisis

This paper simulates the macroeconomics of Greece following its 2009 government debt crisis that precipitated a 4-year depression with stagnant growth since. A model of aggregate supply and demand estimated with quarterly data from 2003 to 2018 is constrained to a balanced government budget, outside euro exchange rate, and exogenous international interest rate. Dynamic stochastic simulations starting in 2011 capture the effects of less erratic government spending, quicker transition to debit cards, and returning investment sentiment to the pre-crisis level. Simulations track the path of income along with the trade balance, tax revenue, price level, and equilibrium quantity of money.