Aggregate Demand Model Research Articles

ГОСУДАРСТВЕННЫЕ ЗАКУПКИ КАК ИНСТРУМЕНТ ПРОВОДИМОЙ МАКРОЭКОНОМИЧЕСКОЙ ПОЛИТИКИ (НА ОСНОВЕ МОДЕЛИ «СОВОКУПНЫЙ СПРОС – ИНФЛЯЦИОННАЯ НАСТРОЙКА» AD–IA)

The article considers the application of the Keynesian model of aggregate demand – inflationary adjustment on the example of data analysis of changes in the macroeconomic parameters of the economic development of the Russian Federation. It describes and proves the relationship between the level of gross domestic product, total domestic consumption, investment and net exports due to changes in the amount of public procurement in different periods. The theoretical justifications for the model’s action due to changes in the inflationary setting are revealed, and the assumption about changes in inflation due to changes in the gross domestic product is expressed and verified (the reverse situation). The theoretical conclusions are supported by appropriate graphical methods of presenting information for greater clarity.

Investopedia Needs to Heavily Revise Its ‘IS-LM Model’ Paper

Investopedia Needs to Heavily Revise Its ‘IS-LM Model’ Paper

Distribution and Gender Effects on the Path of Economic Growth: Comparative Evidence for Developed, Semi-Industrialized, and Low-Income Agricultural Economies

This paper applies a robust empirical methodology, which considers issues relating to cross-country heterogeneity and cross-sectional dependence, to inspect the contributions of gender equality and factor income distribution to an economy's growth path. A dynamic model of aggregate demand is estimated on a unique panel dataset from 46 countries that are further grouped into developed (DC), semi-industrialized (SIEs), and low-income agricultural economies (LIAEs). The empirical findings suggest that, overall, growth is driven by investment in the short run and domestic demand in the long run. In the short run, the results suggest that low female wages act as a stimulus to growth in SIEs but may promote contractionary pressures on demand in the long run. For LIAEs and DCs, the effect of improved labor market conditions for women--leaving men's constant--on demand-led growth conditions are positive in the short run but may harm long-term growth prospects. In all, the empirical evidence, combined with the stylized facts about institutional and economic inequality, suggests that the impact of gender and income inequality on macroeconomic outcomes will differ depending on the economic structure and level of economic development.

Analysing policies to increase graduate population: do tuition fees matter?

ABSTRACT Although broadening equal access to higher education has been an objective public policy for decades, little is known about the effectiveness of alternative means for achieving this goal. Moreover, it has raised a need of explaining the heterogeneity in Higher Education attainment across European countries, where high level of graduate population can be observed both in the presence of high- and low-levels of fees. This paper surveys the extant literature providing some background on the economic concepts of higher education market, and reviews key determinants of demand and supply. A theoretical and empirical model of aggregate demand and supply of higher education is derived, with the aim to facilitate the understanding of the challenges in today’s higher education systems, as well as the opportunities for development. The model is validated on some exemplary case studies describing different relationships between the level of public investment and levels of graduate population.

Competitive Analysis among Multi-product Firms

We analyze and study competition in differentiated product market using public data source. Understanding competitive market structure is critical for firms to assess how their products compete against other firms in a given market. In this paper, we estimate consumer demand, extend clout and vulnerability framework, and study competition among multi-product manufacturers in differentiated product market. For our empirical analysis, we adopt choice-based aggregate demand model and estimate consumer demand while accounting for unobserved product characteristics. Once we estimate consumer demand, we compute full price elasticity matrix and investigate intra- and inter- manufacturer substitutions among consumers. This research offers a framework for marketers to analyze and understand market structures, leading them to informed decisions.

Competitive Analysis among Multi-product Firms

We analyze and study competition in differentiated product market using public data source. Understanding competitive market structure is critical for firms to assess how their products compete against other firms in a given market. In this paper, we estimate consumer demand, extend clout and vulnerability framework, and study competition among multi-product manufacturers in differentiated product market. For our empirical analysis, we adopt choice-based aggregate demand model and estimate consumer demand while accounting for unobserved product characteristics. Once we estimate consumer demand, we compute full price elasticity matrix and investigate intra- and inter- manufacturer substitutions among consumers. This research offers a framework for marketers to analyze and understand market structures, leading them to informed decisions.

La demanda agregada de la cultura en México: propensión al consumo y tasa de interés para empresas culturales

El presente trabajo es un ejercicio macroeconómico a partir de la información del Sistema de Cuentas Satelitales de la Cultura de México, que publica el Instituto Nacional de Estadística y Geografía (INEGI), considerando la contabilidad económica en el ramo. El objetivo es determinar un modelo de demanda agregada del sector de la cultura, a partir del cálculo de una propensión marginal al consumo y de una tasa de interés para empresas culturales. Para lograr la meta, se considera la literatura macroeconómica tradicional para deducir el gasto autónomo propio del ramo y, con ello, la curva de bienes culturales. También se toma en cuenta la presencia de la curva del mercado de dinero para obtener el propósito señalado. Se utilizan Mínimos Cuadrados Ordinarios (MCO) y, en el caso de presencia de heterocedasticidad, Mínimos Cuadrados Ponderados (MCP). Se concluye que la población mexicana, en promedio, no gasta más allá del 5.3% de sus ingresos en bienes culturales y que las empresas creativas, por sus mismas condiciones, requieren de tasas de interés muy por debajo de las del total del mercado financiero.

Prudential Monetary Policy

Should monetary policy have a prudential dimension? That is, should policymakers raise interest rates to rein in financial excesses during a boom? We theoretically investigate this issue using an aggregate demand model with asset price booms and financial speculation. In our model, monetary policy affects financial stability through its impact on asset prices. Our main result shows that, when macroprudential policy is imperfect, small doses of prudential monetary policy (PMP) can provide financial stability benefits that are equivalent to tightening leverage limits. PMP reduces asset prices during the boom, which softens the asset price crash when the economy transitions into a recession. This mitigates the recession because higher asset prices support leveraged, high-valuation investors' balance sheets. An alternative intuition is that PMP raises the interest rate to create room for monetary policy to react to negative asset price shocks. The policy is most effective when there is extensive speculation and leverage limits are neither too tight nor too slack. When shadow banks are present, PMP can still replicate the benefits of macroprudential policy, but PMP is less effective (like macroprudential policy) because shadow banks respond by increasing their leverage.

Is the Simple Price Premium that Simple?

Abstract Brand equity has been a perennial topic in marketing. Among all types of measures, price premium is widely accepted due to its simple yet efficient characteristics. However, there is some disagreement regarding whether this measure captures enough facets of brand equity and whether price premium is an appropriate measure to reflect the market position of a brand. With current technique developments, more sophisticated brand equity measures have been developed. A natural question arises as to whether more sophisticated measures are better than price premium. Using large-scale national scanner data covering 47 major U.S. markets, we employ the aggregated demand model to estimate a complex brand equity measure and compare it with price premium. Our results suggest that the simple price premium is consistent with the complex measure under certain conditions. We provide managers with suggestions regarding choosing the most appropriate brand equity measures to signify their brands’ values.

Modeling of bidding strategies in a competitive electricity market: A hybrid approach

AbstractIn the paper, an innovative hybrid algorithm is proposed to solve bidding strategy problem in electricity market. The proposed hybrid technique is the combination of the recurrent neural network (RNN), support vector machine (SVM), and the lightning search algorithm (LSA). The main contribution of this paper is to maximize the profits of suppliers and minimize the customer payments; it is very important to create reasonable matching rule for the electricity market. LSA optimizes bidding coefficients of both the suppliers and consumers with the consideration of available power generation limit, power demand, market‐clearing price (MCP), and constraints. RNN is utilized for demand prediction at every hour, and SVM ensures the MCP based on the demand. The proposed bidding strategy ensures the maximum profit of the suppliers and consumers because of the aggregated demand model. The proposed method is tested on The Institute of Electrical and Electronics Engineers (IEEE) 30‐bus system and 75‐bus Indian practical system and compared with the existing techniques. The comparison results demonstrate the superiority of the proposed technique and confirm its potential to solve the problem. Also, the proposed model and the strategies are implemented in the MATLAB, and the performance will be studied under various demand environments.

A multi-scale calibration approach for process-oriented aggregated building energy demand models

Long-term energy planning relies largely on projections of future energy demand and hourly load profiles. Aggregate building models are increasingly being utilized to characterize the sensitivity of current and future building stocks to changes in climate, population, and building technology on city-to-regional-to-national scales. Due to challenges in the availability of data, those analyses have been limited to projection of energy demand at a single scale, usually state or country, while long-term planning power system models and production cost models might operate at different spatial scales such as energy regions which are focused on ensuring adequate generation infrastructure. We propose and evaluate a novel method to calibrate an aggregate building energy demand model (PNNL's BEND model) against the best available data at the spatial scale of balancing authorities. This approach extends previous work on aggregated building energy demand by facilitating analysis of building energy demand across scales, in particular policy and operational decision-making scales. We show that the bias-corrected model estimates building electric loads reasonably well compared with estimates from a statistical model, but has the additional feature of flexibility across spatial scales. While the calibration approach is presently U.S.-centric and associated with U.S. energy regions, it can be extrapolated to other worldwide regions with similar scale challenges between policy and operational implementation decision making. We discuss the significant challenges involved in formulating and calibrating a complex physical model based on simulations of roughly 100,000 individual buildings against available aggregate regional electric load data and highlight areas for potential future work and improved data collection.

Instability, imprecision and inconsistent use of equilibrium real interest rate estimates

The debate on monetary and fiscal policy is heavily influenced by estimates of the equilibrium real interest rate. In particular, this concerns estimates derived from a simple aggregate demand and Phillips curve model with time-varying components as proposed by Laubach and Williams (2003). For example, Summers (2014a) refers to these estimates as important evidence for a secular stagnation and the need for fiscal stimulus. Yellen (2015, 2017) has made use of such estimates in order to explain and justify why the Federal Reserve has held interest rates so low for so long. First, we re-estimate the United States equilibrium rate with the methodology of Laubach and Williams (2003). Then, we build on their approach and an alternative specification to provide new estimates for the United States, Germany, the euro area and Japan. Third, we subject these estimates to a battery of sensitivity tests. Due to the great uncertainty and sensitivity that accompany these equilibrium rate estimates, the observed decline in the estimates is not a reliable indicator of a need for expansionary monetary and fiscal policy. Yet, if these estimates are employed to determine the appropriate monetary policy stance, such estimates are better used together with the consistent estimate of the level of potential output.

Prudential Monetary Policy

Should monetary policymakers raise interest rates during a boom to rein in financial excesses? We theoretically investigate this question using an aggregate demand model with asset price booms and financial speculation. In our model, monetary policy affects financial stability through its impact on asset prices. Our main result shows that, when macroprudential policy is imperfect, there are conditions under which small doses of prudential monetary policy (PMP) can provide financial stability benefits that are equivalent to tightening leverage limits. PMP reduces asset prices during the boom, which softens the asset price crash when the economy transitions into a recession. This mitigates the recession because higher asset prices support leveraged, high-valuation investors’ balance sheets. The policy is most effective when the recession is more likely and leverage limits are neither too tight nor too slack. With shadow banks, whether PMP “gets in all the cracks” or not depends on the constraints faced by shadow banks.

Positive Slope Model of Aggregate Demand

Abstract This paper analyzes Internal Aggregate Demand. This aggregate, along with other production indicators, is the main indicator of the country’s economic performance rate. Objective analysis is important for their perspective, as well as for a set of other related indicators, such as inflation rate, unemployment rate, etc. In economic theory, the Aggregate Demand Curve (AD) deals with negative slope. At the point where AD interrupts the AS (aggregate supply curve) there is macroeconomic equilibrium. Creating this equilibrium, shifting curves, creates a number of other figures that show how the level of output, prices and employment will be, and overall the level of economy in the future. In this study, with the data of the Albanian economy, was built, for a period of 17 years, the Internal Demand Curve. Three effects are analyzed: the real balance sheet effect, the interest rates and the external trade effect. The internal demand curve has resulted in a Positive Slope. The equilibrium is not created at the intersection point of the curves. These curves stand facing each other. The equilibrium is set by the different aggregate price level. The Gross Domestic Product Curve (GDP) is the equilibrium curve created by the interaction of Aggregate Demand and Aggregate Supply. This position is real, and creates opportunities for objective analysis of the economy. This paper uses econometric, statistical, comparative and synthesis methods.

Price Trends and Dynamic Pricing in Perishable Product Market Consisting of Superior and Inferior Firms

We consider the problem of a firm that sells perishable products with a dynamic pricing scheme in the presence of a firm offering a superior product. We provide a probabilistic characterization of the optimal price process under the existence of such a firm for an aggregate demand model and for a multinomial logit demand model. Our results demonstrate that if the seller takes the price of the other firm into account in their optimal policy, then the optimal price process tends to increase over time before the inventory level falls to one, after which it decreases. Otherwise, the price process decreases and then increases (this path is called a J-shaped curve) before the inventory level falls to one if the price of the other firm is relatively low and the customer’s valuation remains unchanged over time early in the sales period. We also demonstrate numerically that when the firm uses a monopolistic policy and the difference in service quality between the two firms is large, the switching time between the downward and upward trends takes place in the early stage of the sales period and in particular this J-shaped phenomenon is strongly observed.

How Rewarding is the Reward? Demand Estimation of Crowdfunding Platforms

Reward-based crowdfunding platforms are best known to facilitate the fund-raising process for entrepreneurs and small businesses. Entrepreneurs seek money from the backers to kick off their projects in exchange for rewards. While the competition among the projects to get more supporters grow, many projects fail to reach their fund-raising target. We use a structural demand estimation to understand the role of different aspects of reward scheme design and pricing. More specifically, we apply an aggregate level discrete choice demand model on Kickstarter projects. We characterize the features of the projects by utilizing the document embedding vectors from natural language processing methods. We treat the endogeneity of the price by applying latent instrument variables and finite mixture model for price. The results show that the price coefficient is biased towards zero in the absence of endogeneity treatment. On the reward scheme design, we show low-level rewards cannibalize the more expensive ones. We also find that low-level rewards have the least contribution in customer welfare. Campaign creators and online platforms benefit from the insights of the model for reward scheme design and pricing.

A Descriptive Model of Banking and Aggregate Demand

We integrate a banking sector into an accessible macroeconomic framework, which then provides new insights on developments around the Global Financial Crisis. The analysis shows that growth of banking sector money supply may help explain the secular decline in long-term interest rates before the crisis. A new bank funding channel of monetary transmission clarifies why increases in central bank policy rates could not reverse this trend. Our analysis highlights the distinction between the zero lower bound and the liquidity trap, and shows that bank recapitalizations can be more effective than fiscal expansions in restoring aggregate demand after a banking crisis.

Bridging the Gap between Economic Modelling and Simulation: A Simple Dynamic Aggregate Demand-Aggregate Supply Model with Matlab

This paper aims to connect the bridge between analytical results and the use of the computer for numerical simulations in economics. We address the analytical properties of a simple dynamic aggregate demand and aggregate supply (AD-AS) model and solve it numerically. The model undergoes a bifurcation as its steady state smoothly interchanges stability depending on the relationship between the impact of real interest rate on demand for liquidity and how fast agents revise their expectations on inflation. Using code embedded into a unique function in Matlab, we plot the numerical solutions of the model and simulate different dynamic adjustments using different parameter values. The same function also accommodates the analysis of the impacts of fiscal and monetary policy and supply side shocks on the steady state and the transition dynamics of the model.

Fuzzy EOQ model of a high technology product under trial-repeat purchase demand criterion

Accurate prediction and knowledge of adoption pattern is critical to formulate inventory strategies for any technology product. Prior researches in this area recommended that aggregate level demand models often forecast imprecise sales figure. We argue that it is essential to recognize the technology specific adoption dynamics prior to formulate the inventory strategies. This paper aims to develop an Economic Order Quantity (EOQ) model to find strategy for a firm that sells technology products’ over a defined planning horizon. Demand is considered to follow trial-repeat purchase phenomenon. The fuzzy criterion is incorporated to address the problems of uncertain nature of marketing parameters. The model is illustrated with a numerical example and a comprehensive sensitivity analysis on the optimal solution with respect to different parameters has also been performed.

Development of railway station choice models to improve the representation of station catchments in rail demand models

ABSTRACTThis paper describes the development of railway station choice models suitable for defining probabilistic station catchments. These catchments can then be incorporated into the aggregate demand models typically used to forecast demand for new rail stations. Revealed preference passenger survey data obtained from the Welsh and Scottish Governments was used for model calibration. Techniques were developed to identify trip origins and destinations from incomplete address information and to automatically validate reported trips. A bespoke trip planner was used to derive mode-specific station access variables and train leg measures. The results from a number of multinomial logit and random parameter (mixed) logit models are presented and their predictive performance assessed. The models were found to have substantially superior predictive accuracy compared to the base model (which assumes the nearest station has a probability of one), indicating that their incorporation into passenger demand forecasting methods has the potential to significantly improve model predictive performance.