Aggregate Demand Model Research Articles

J M Keynes's Main Argument in the General Theory is Not Expressed in Terms of His Aggregate Demand (D) and Aggregate Supply (Z) Model. Keynes's D-Z Analysis Supports a Specific Y=C I, Marginal Propensity to Consume, Income Expenditure, Investment Multiplier Result (I=S) that Keynes Combined with His Liquidity Preference Function (L=M) to Determine the Rate of Interest in His IS-LP

Keynes’s Theory of Effective Demand model of Expected Aggregate Demand (D) and Expected Aggregate Supply (Z) was used by Keynes to construct the Aggregate Supply Curve (ASC), which is a locus of the set of all possible expected D=Z equilibrium results that satisfy the necessary and sufficient first and second order conditions for an expected profit maximum in the output market. Only one D=Z combination will be optimal and provide a full employment level of output at non inflationary levels so that there will be no involuntary unemployment in the labor market. All other equilibriums from the ASC will not provide a full employment level of output at non inflationary levels. There will be some amount of involuntary unemployment that will show up as a disequilibrium in the labor market. Only one of the set of D-Z equilibriums will be the actually realized result. This actually realized value of D (=D1 plus D2) is called Y by Keynes. This gives a specific actual, realized Y=C plus I, marginal propensity to consume, Income expenditure, Investment Multiplier result (I=S) that Keynes combined with his Liquidity Preference Function (L=M) to determine the Rate of Interest in his IS-LP (LM) model of chapters 15 and 21. Thus, the IS-LP (LM) model is primary while the D-Z model is secondary. Both models are needed since Y, aggregate Income, is used in the IS-LP (LM) model. Y is provided by the D-Z model. The Neoclassical Synthesis Keynesians have correctly emphasize the IS-LP (LM) model as being the major result of the General Theory, but overlooked that it was Keynes, and not Hicks, Harrod, Meade or anyone else, who originated, taught, developed and applied the IS-LP (LM) model. However, the Neoclassical Synthesis Keynesians have also overlooked the full D-Z model provided by Keynes in chapter 20 of the General Theory and concentrated on chapter 3, which has no D-Z analysis in it. The Post Keynesians have, incorrectly, ignored Keynes’s IS-LP(LM) model, painstakingly constructed sequentially by Keynes in chapters 10, 11, 13, 14, 15, 16, 17, and 21 and concentrated on the introductory chapter 3 of the General Theory alone, which only contains a brief outline of the D-Z model. Keynes fully develops the D-Z model in chapters 20 and 21 of the General Theory. What Keynes did in chapters 19-21 is ignored by the Post Keynesians. Thus, Keynes’s complete contribution in the General Theory, which involves both the IS-LP (LM) model and the D-Z model, has never been acknowledged. This is the result of the vast confusion about “What did Keynes really mean in the General Theory” that can be traced to three main sources-Joan Robinson, Austin Robinson, and Richard Kahn.

Hospital Quality and Demand: An Analysis of German Hospitals Using Distance-Metric Approach

Bu makalede, zorunlu olarak yayimlanan kalite raporlarindan elde edilen cesitli kalite olculeri kullanilarak, Alman hastaneleri icin bir toplam talep modeli tahmin edilmistir. Bu tahmin yapilirken, Mesafe-Metrigi yaklasimi benimsenmistir. Sonuclara gore, kadin dogum alaninda talep, bazi klinik kalite olculerine karsi duyarlidir. Son olarak ampirik sonuclar hastane talebinde, yakinlardaki rakip hastanelerin klinik kalitesinden ortaya cikan zayif tasma etkilerine isaret etmektedir

AN EQUILIBRIUM AGGREGATE DEMAND AND SUPPLY MODEL TO EXAMINE THE DYNAMIC EFFECT OF OIL PRICE SHOCKS ON OUTPUT AND INFLATION IN IRAN AS AN OIL EXPORTING COUNTRY

Iran is an oil exporting country in Middle East. The high share of the oil revenues in Iran is a serious economic problem. Due to the high dependency of Iran’s economy on oil revenues, oil price shocks have a determinant impact on macroeconomic variables. In this paper, we analyze the dynamic effects of oil price shocks and the aggregate supply and aggregate demand shocks on macroeconomic fluctuations in Iran. According to macroeconomic theory and aggregate demand and supply model in equilibrium, a structural vector autoregressive (VAR) model is applied to identify different structural shocks and further assess the relative contributions of different shocks on macroeconomic fluctuations, using a decomposition approach. The results show that oil price shocks have significant and positive effects on both output and inflation. Aggregate supply and aggregate demand shocks are the main causes of fluctuation in output and inflation, and moreover, the effect of aggregate supply shocks on output is permanent in the Iranian economy. On the base of this study results, we suggest the Iranian government should accelerate the economic reforms such as the finance system of state owned enterprises, the tax system, the cash subsidy distribution system, the allocation system of the government budget in national and provincial level, the financial and banking system, and so on. The suggested reforms aim to decrease in the share of oil revenues in the economy and protect the Iranian economy in the face of any exogenous and endogenous shocks.

Heterogeneity in demand for performances and seats in the theatre

Studying the heterogeneity of consumers allows to price the product differently for consumer segments or groups of a product. In this paper, we estimate a model of aggregate demand for Perm Opera and Ballet Theatre focusing on the heterogeneity in price effect on demand for tickets on different performances and seats. We estimate the parameters of demand function using censored quantile regression that accounts for the limited capacity of the theatre house. We reveal the price effect variation across different types of theatrical productions and seats with lower elastic demand on ballets and for seats of higher quality.

Counterfactual Estimation in Semiparametric Multinomial Choice Models

We show how to construct bounds on counterfactual choice probabilities in semiparametric discrete-choice models. Our procedure is based on cyclic monotonicity, a convex-analytic property of the random utility discrete-choice model. These bounds are useful for typical counterfactual exercises in aggregate discrete-choice demand models. In our semiparametric approach, we do not specify the parametric distribution for the utility shocks, thus accommodating a wide variety of substitution patterns among alternatives. Computation of the counterfactual bounds is a tractable linear programming problem. We illustrate our approach in a series of Monte Carlo simulations and an empirical application using scanner data.

Counterfactual Evaluation in Semiparametric Multinomial Choice Models

We propose using cyclic monotonicity, a convex-analytic property of the random utility choice model, to derive bounds on counterfactual choice probabilities in semiparametric multinomial choice models. These bounds are useful for typical counterfactual exercises in aggregate discrete-choice demand models. In our semiparametric approach, we do not specify the parametric distribution for the utility shocks, thus accommodating a wide variety of substitution patterns among alternatives. Computation of the counterfactual bounds is a tractable linear programming problem. We illustrate our approach in a series of Monte Carlo simulations and an empirical application using scanner data.

Inference for Product Competition and Separable Demand

This paper presents a methodology for identifying demand groups and measuring competition for differentiated products using store-level sales data. We use the concept of economic separability as an identification condition for different product groups, and build a weakly separable model of aggregate demand. One common issue with separable demand models is that the partition of products into separable groups must be known a priori, which severely shrinks the set of admissible substitution patterns. This paper relaxes this assumption and allows the partition to be an estimated model parameter. We focus on estimating partitions within a log-log demand system where weak separability induces equality restrictions on a subset of cross-price elasticity parameters. An advantage of our approach is that we are able to find groups of separable products rather than just test whether a given set of groups is separable. Our method is applied to two aggregate, store-level data sets. The first is in the jams, jellies, and spreads category where the nature of competition between products is straightforward. The second is within the juice category where the structure of demand is less obvious. We find that the estimated demand groups do not necessarily coincide with predefined category labels. Our approach also provides gains in efficiency and predictive ability over unrestricted models, and is useful for answering questions about brand positioning and the boundaries of product competition.

Tourist seasonality and the role of markets

Abstract This paper proposes three methodologies for measuring and analyzing tourist seasonality from a market-side perspective and empirically implements them for Spain as a whole. Firstly, seasonality is analyzed by means of monthly concentration indexes and the coefficient of variation is especially recommended. Secondly, the role of markets is explored through an additive inequality decomposition technique. Thirdly, the primary economic determinants of tourist seasonality are assessed through a dynamic panel data model. The main results are firstly that seasonality in Spain has worsened since 2008, coinciding with a strong growth in overall demand; secondly that three markets generate two thirds of the seasonality, with the pattern of the UK tourists of special concern; and thirdly that aggregate demand models suggest that prices, exchange rates and especially income levels are significant explanatory factors. The authors believe that the methodologies used, and the country-specific results obtained, are broadly applicable in marketing and tourist public strategies.

Financial Development Influence on Economic Growth in Albania

During the 2000s the private banking sector in Albania started to consolidate and the level of lending in the economy started to grow. In the same period the overall economic indicators were showing positive growth too, but that all changed after the financial crisis of 2008. It took a while for its effects to hit the country but when they came the economy started to slowdown and the banks while facing a rise in Non-Performing Loans (NPL) started to cut out lending. The drop on lending is considered a problem by policy makers who see a pattern of causality in the finance – growth nexus based on theoretical works saying that finance development can influence growth. Even though the theory linking economic growth with financial development is not unanimously accepted on academic circles, empirical studies support the fact that a better developed financial system helps to support a sustainable growth. This seems enough to keep policy makers concerned with keeping lending high in the economy. The purpose of this study is to find if there is a pattern of such correlation between lending and growth in the Albanian economy. For the purpose data from the last 21 years have been analyzed through a time series regression where per capita GDP growth rate is the dependable variable and the domestic credit to private sector by banks is undependable variable. For the analyze is based on the aggregate demand model where credit is influencing investments, the influence which government spending may have on output is tested it the regression as an influential factor. The result showed that the explanatory variable coefficient is negative, suggesting that in this case the financial sector growth has a negative effect on growth. We assume this is so because the main channel through which the finance influences growth, which is by allocating capitals towards the most efficient opportunities, is not actually working and this can be seen by the high number of non-performing loans on the banks’ balance sheets.

Cost and time damping: evidence from aggregate rail direct demand models

There is a significant body of evidence from both disaggregate choice modelling literature and practical travel demand forecasting that the responsiveness to cost and possibly to time diminishes with journey length. This has, in Britain at least, been termed ‘Cost Damping’, and is recognised in guidance issued by the UK Department for Transport. However, the consistency of the effect across modes and data types has not been established. Cost damping, if it exists, affects both the forecasting of demand and our understanding of behaviour. This paper aims to investigate the evidence for cost and time damping in rail demand using aggregate rail ticket sales data. The rail ticket sales data in Britain has, for many years, formed the basis of analysis of a wide range of impacts of rail demand. It records the number of tickets sold between station pairs, and it is generally felt to provide a reasonably accurate reflection of travel demand. However, the consistency of these direct demand models with choice modelling and highway demand model structures has not been investigated. Rail direct demand models estimated by ticket sales data indicate only slight variation in the fare elasticity with distance, as is evidenced in the largest meta-analysis of price elasticities conducted to date (Wardman in J Transp Econ Policy 48(3):367–384, 2014). This study of UK elasticities shows strong variation between urban and inter-urban trips, presumably a segmentation at least in part by purpose, but less remaining variation by trip length. A lack of variation by length supports the hypothesis of cost damping, because constant cost sensitivity would imply that fare elasticity would increase strongly with distance, because of the increasing impact of higher fares at longer distances. In this paper we indicate that rail direct demand models have some consistency of behavioural paradigm with utility based choice models used in highway planning. We go on to use rail demand data to estimate time and fare elasticities in the context of various cost damping functions. Our empirical contribution is to estimate time elasticities on a basis directly comparable with cost elasticities and to show that the phenomenon of cost damping is strongly present in ticket sales data. This finding implies that cost damping should be included in models intended for multimodal analysis, which may otherwise give incorrect predictions.

Oil price volatility and fiscal policies in oil‐exporting countries

AbstractThe meteoric decline in oil price in late 2014, a manifestation of crude oil price volatility, pressured the fiscal positions of many oil‐exporting countries (OECs). This study examined the relationship between oil price volatility and OECs’ fiscal policy [proxied by primary fiscal balance (PFB)] responses. It estimated a small open‐economy aggregate demand model in which oil price is externally determined. Using various measures of oil price volatility in a vector error correction (VEC) model, this study established that fiscal policies in OEC were not procyclical but driven by oil price volatility. Oil price volatility reduced PFB in the short run. In the long run however, PFB rose in response to price volatility, suggesting that OECs’ governments eventually consolidate their fiscal positions to reduce short‐run fiscal deficit induced by oil price volatility. Though their fiscal policies were pressured in the short run, OECs were able to stabilise their fiscal dynamics in the long run.

A Descriptive Model of Banking and Aggregate Demand

We integrate a banking sector into an accessible macroeconomic framework, which then provides new explanations for developments around the Global Financial Crisis. The analysis shows that growth of banking sector money supply may explain the secular decline in long-term interest rates before the crisis. A new bank funding channel of monetary transmission clarifies why even large increases in central bank policy rates could not reverse this trend. Our analysis challenges the view that monetary policy becomes ineffective in a liquidity trap, and shows that bank recapitalizations are more effective than fiscal expansions in restoring aggregate demand after a banking crisis.

Optimal Bidding strategy in South Region Day-ahead Market Model using New Aggregated Demand Model and Hybrid Technique

In this paper a half breed calculation (ABC_PSO) comprising of Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO) in light of demonstrating for the ideal offering systems in an aggressive power force business sector is proposed. We set forward a novel enhanced strategy which enhances the Profit of the suppliers. In the aforementioned technique ideal using so as to offer parameters are controlled the two periods of the Artificial Bee Colony (ABC). From the streamlined parameters the definite arrangement is anticipated by utilizing third phase of the ABC calculation i.e scout honey bee. Here, the honey bee's populace speed and the position vector are enhanced by utilizing the method of PSO rather than Scout honey bee, to locate the precise offering parameters. The Indian Energy Exchange (IEX) hourly based burden request dataset is utilized for using so as to foresee the heap Artificial Neural Network (ANN) system. At long last the proposed system is executed in the MATLAB/simulink stage and viability is investigated by utilizing the correlation of distinctive procedures like Artificial Bee Colony (ABC) calculation, Particle Swarm Optimization (PSO) calculation, ABC_PSO. The aftereffects of examination exhibited the prevalence of the proposed approach and affirm its capability to take care of the issue.

Probabilistic generation of time‐coupled aggregate residential demand patterns

For distribution system studies, a relevant aspect is the characterisation of the aggregate demand in a feeder. The probabilistic model of the aggregate demand is very useful for system operators or aggregators to extract information about the demand side behaviour in the operation of smart grids and microgrids. The time step used to scan the aggregate demand pattern is very important to preserve the information about the consumers’ behaviour and the related uncertainty. The conventional models of aggregate electrical demand consider an average value for a specific time step (e.g. 30 min to 1 h). In this study, a faster time step (1 min) is considered to construct a time-coupled probabilistic model of the aggregate residential demand based on Beta distributions. For a given number of aggregate loads, the parameters of the Beta distributions are found by taking into account the aggregate demand pattern variations at two successive time steps. The probabilistic model is then used to generate a number of aggregate demand scenarios. The effectiveness of the proposed scenario generation method is evaluated by using goodness of fit tests such as the Kolmogorov–Smirnov test and the average mean absolute percentage error.

Quality vs. variety: Trading larger screens for more shows in the era of digital cinema

Movie exhibitors currently face two forces vying for the limited footprint of their properties. Recent advances have enabled exhibitors to satisfy consumers' long-standing desire for increasingly larger screens. On the other hand, digital tech- nology has reduced the cost of playing the same movie on multiple screens, thereby creating an incentive for screen proliferation to increase the number of show times for a given movie. Increasing the screens also has the added benefit of allowing the exhibitor to expand the number of unique movies screened at a given time. This is fundamentally a tradeoff between quality (larger screen size) and variety (more movies or showings). The goal of this paper is to evaluate consumers' relative valu- ations of the large screens vs. more shows tradeoff. We use a new data set on movie showings in India at the movie-chain-market-week level to estimate an aggregate discrete-choice demand model providing measures of customer preferences for the number of movie showings and screen size. India provides a valuable setting to study this question because the densely populated cities face substantial space constraints and regional heterogeneity in tastes and languages suggest the option of more shows may be more important in some cities than others. Our findings suggest that regions which are more urban and have a greater share of people with higher education prefer larger screens (quality) while most other regions prefer more showings (variety).

The International Effects of US Uncertainty

AbstractWe propose domestic uncertainty shocks may serve as a channel through which business cycles are transmitted internationally. To quantify uncertainty, we use two measures from the current literature and estimate vector autoregressions to evaluate the effects US uncertainty shocks have on the Japanese and British economies. Our results suggest that US uncertainty shocks have international effects consistent with a demand shock in the context of an open‐economy aggregate demand and aggregate supply model with sticky prices. Copyright © 2015 John Wiley & Sons, Ltd.

An Estimation of Long-Term Housing Demand Considering Cohort Effect

Most models of aggregate housing demand assume that households follow demand estimated with a single cross-sectional observation. However, housing demand depends not only on the current social and economic context characterized by stage of life course, or the age, but also on the past socio-economic experiences and physical properties differently formed by generations, or the birth cohort. This study proposes a methodology to estimate aggregate housing demand that reflects inter-generational differences of housing consumption. Using the Korean Labor and Income Panel Study (KLIPS) and Korean Census data, a methodology was developed to determine inter-generational differences of housing demand on the basis of a modified Mankiw and Weil (M-W) model. In the model, birth cohort rather than age group of household members are used as exploratory variables. The estimates are then applied to the process to estimate future housing demand. The results reveal that the post baby-boom generations including the baby boomer are reducing their housing consumption compared to previous generations, and that the aggregate housing demand is smaller than what was estimated using the M-W model.

What drives university applications? An attempt to explain aggregate demand for higher education

Low educational attainment is frequently pointed out as a barrier to social and economic development and most governments aim at increasing participation in higher education. However, effective strategies to increase aggregate demand require information on its most relevant determinants, which is difficult to obtain because applications to higher education are usually not organised at the country level. In this study, we utilise a large sample of data on applications available in Portugal to estimate a model of aggregate demand for higher education. Our estimates suggest that the economic context is relatively less relevant than policy orientations, and thus that sustaining or increasing higher education participation may be more dependent on political choice than on economic circumstances. The only relevant economic determinant in the model is unemployment which contradicting some previous research appears to exert a negative impact upon aggregate demand.

Macroéconomie du court terme et politique climatique : quelques leçons d'un modèle d'offre et demande globales

We introduce the concept of carbon footprint into an aggregate demand and supply model with imperfectly competitive price and wage formation. We analyse the properties of the short-term macroeconomic equilibrium in the presence of a climate policy, which may take the form either of a carbon tax or of quotas of pollution permits. We show that in the short run climate policy (or its strengthening) is simultaneously a negative aggregate supply shock and a positive aggregate demand shock. It is thus inflationary but it has an ambiguous impact on aggregate economic activity and employment: it will only stimulate output in an economy where nominal wages are rigid enough. In all cases, climate policy will depress real wages. We also analyse the interactions between climate policy and the usual macroeconomic policies of demand (fiscal and monetary stimuli) and supply (labour tax cut). The multiplier effects of these demand and supply policies depend on the instrument chosen for implementing the climate policy (carbon tax or pollution permits). We finally establish the conditions under which a reform combining a climate policy strengthening and a labour tax cut can reach the double objective of a lower carbon footprint and a lower unemployment rate, without reducing workers’ real wages. Such a policy reform has however an ambiguous impact on the government surplus (or deficit).

Planning sustainable hydrogen supply chain infrastructure with uncertain demand

This study introduces a multi-period optimization model taking into account the stochasticity and the effect of uncertainty in the hydrogen production, storage and usage in macro view (e.g. county level). The objective function includes minimization of total daily social cost of the hydrogen supply chain network with uncertain demand. There are several factors and key attributes, which influence consumer choice to buy a fuel cell vehicle. At the same time, consumer preference on the demand side is the most important factor in predicting changes in the auto market. A spatially aggregated demand model was developed to estimate the potential demand for fuel cell vehicles based on different household attributes such as income, education etc. These models were applied to evaluate the future hydrogen supply chain for State of New Jersey.