estimating residential demand for electricity in greece abstract this paper examines the residential demand for electricity in greece the issues of structural stability price and income sensitivity of both long and short run residential demand for electricity in greece were examined employing monthly data over the period 1986 1999 the long run residential demand for electricity is estimated taking into account changes in weather conditions weighted by the size of the population employing multivariate framework analysis a long run residential demand function for electricity sensitive to real income price level and weather conditions is found to exist and the importance of short run deviations is presented using vector error correction model vecm estimation the empirical evidence suggests the presence of a stable residential demand for electricity in greece both in the long and short run periods and the policy implications of such a relationship are presented

analysis of seat allocation and overbooking decisions with hybrid information abstract we investigate a single leg airline revenue management problem where an airline has limited demand information and uncensored no show information to use such hybrid information for simultaneous overbooking and booking control decisions we combine expected overbooking cost with revenue then we take a robust optimization approach with a regret based criterion while the criterion is defined on a myriad of possible demand scenarios we show that only a small number of them are necessary to compute the objective we also prove that nested booking control policies are optimal among all deterministic ones we further develop an effective computational method to find the optimal policy and compare our policy to others proposed in the literature

average and marginal price changes and the demand for electricity an econometric study the empirical literature on the demand for electricity has hitherto failed to adequately deal with increasing block pricing while it is desirable in principle to include the entire price schedule in the demand function the convention has been to include as an argument either an average or a marginal price yet use of either to the exclusion of the other one leads inter alia to biased estimates of own price elasticity with this in mind a residential demand function is estimated employing both average and marginal price while a number of interesting results emerge it is significant that the coefficient on marginal price is right that is the expected inverse relationship between the quantity of electricity demanded and the marginal price it obtains on the other hand the positive sign on average price is troubling because average price is in this case exactly the same concept as the intra marginal payment a change in average price is exactly the same concept as a change in real income t

subjective interest rate uncertainty and the macroeconomy a cross country analysis abstract we ask whether uncertainty about interest rates is important for economic activity the effects of interest rate uncertainty on the economy are examined through the lens of a small var where the assumption that uncertainty can affect real activity contemporaneously but not vice versa is indeed in line with the data our measure of uncertainty stems from professional forecasts of short and long term interest rates and accounts for both disagreement among forecasters and the perceived variability of future aggregate shocks studying a panel of countries we find that subjective interest rate uncertainty has large negative and persistent effects on the economy

macroeconomic uncertainty through the lens of professional forecasters abstractwe analyze the evolution of macroeconomic uncertainty in the united states based on the forecast errors of consensus survey forecasts of various economic indicators comprehensive information contained in the survey forecasts enables us to capture a real time measure of uncertainty surrounding subjective forecasts in a simple framework we jointly model and estimate macroeconomic common and indicator specific uncertainties of four indicators using a factor stochastic volatility model our macroeconomic uncertainty estimates have three major spikes has three major spikes aligned with the 1973 1975 1980 and 2007 2009 recessions while other recessions were characterized by increases in indicator specific uncertainties we also show that the selection of data vintages affects the estimates and relative size of jumps in estimated uncertainty series finally our macroeconomic uncertainty has a persistent negative impact on real economic activity rather than producing wait and see dynamics

joint estimation of household and heat pump electricity demand statistical methods are applied to analyze metered heat pump and total household loads for residential dwellings the metered loads are combined with other information about the household to study usage patterns equipment energy use is a function of various determining factors and statistical methods are appropriate to reveal the underlying functional relationships a consequence of this approach is that extensive information on households should be gathered whenever metering studies are performed in order to facilitate econometric analysis of the data

electricity demand estimates under increasing block rates using price variables calculated at observed consumption levels this study finds significant bias in ordinary least squares estimates of price elasticities of electricity demand the bias is most severe for specifications using observed average price the finding is important for future econometric work since this type of rate structure is becoming more common the evidence indicates that inappropriate use of ordinary least squares ols overestimates that rate structure premium effect on demand and may underestimate the marginal price elasticity the use of an instrumental variables technique applied to actual rate schedules proves consistent parameter estimates regardless of the rate structure 20 references 3 tables

market structure and the value of overselling under stochastic demands in the operations management literature traditional revenue management focused on pricing and capacity allocation strategies in a two period model with stochastic demand inspired by travel and lodging industries we examine a two period model in which each seller may also adopt the overselling strategy to customers whose valuations are differentiated by timing of arrivals widely seen as a popular hedge against consumers skipping reservations we extend the stylized approaches of biyalogorsky carmon fruchter and gerstner 1999 and lim 2009 to understand the value of overselling under various market structures we find that contrary to existing literature the impact of period two pricing competition from overselling spills over to period one such that overselling may not always be a weakly dominant strategy once unlimited early demand ceases to hold in a duopoly regime we provide some numerical studies on the existence of multiple equilibria at the capacity allocation level which actually lead to different selling strategies at the equilibrium despite identical market conditions and firm characteristics

a survey on risk averse and robust revenue management abstract many industries use revenue management to balance uncertain stochastic demand and inflexible capacity popular examples include airlines hotels car rentals retailing and manufacturing the classical revenue management approaches considered in theory and practice are based on two assumptions first demand as the only uncertain variable follows a known distribution and second risk neutrality justifies the maximization of expected revenue recently two related streams of literature emerged that do not need these assumptions research on risk averse revenue management acknowledges that in practice many decision makers are risk averse research on robust revenue management focuses worst case scenarios without a known demand distribution which is especially relevant for new and extremely unstable businesses this paper motivates the consideration of risk averse and robust revenue management we briefly introduce revenue managements two main methods capacity control and dynamic pricing in the classical risk neutral setting then we provide an exhaustive review of the literature on risk averse and robust capacity control and dynamic pricing in doing so the relevant decision criteria are briefly introduced finally possible avenues for future research are outlined

on the specification of price in studies of consumer demand under block price scheduling using a new model formulation and data from a sample of colorado utilities we investigated the price specification controversy marginal price versus average revenue when estimating residential water demand the improved statistical fit using average

dynamic effects of monetary policy shocks on macroeconomic volatility we use a simple new keynesian model with firm specific capital non zero steady state inflation long run risks and epstein zin preferences to study the volatility implications of a monetary policy shock an unexpected increase in the policy rate by 150 basis points causes output and inflation volatility to rise around 10 above their steady state standard deviations var based empirical results support the model implications that contractionary shocks increase volatility the volatility effects of the shock are driven by agents concern about the in ability of the monetary authority to reverse deviations from the policy rule and the results are re enforced by the presence of non zero trend inflation

dynamic demand for residential electricity in taiwan under seasonality and increasing block pricing abstract this paper studies the dynamic demand for residential electricity in taiwan employing a monthly panel data set composed of 19 counties and spanning the period from 2007 01 to 2013 12 the partial adjustment model used addresses the endogeneity of the electricity price that results from the increasing block pricing the estimated results show that there is a significant seasonal difference in the demand for electricity between the summer and non summer periods both the adjustment speed and own price elasticity during the summer months are found to be lower than those in the non summer months due to the hot weather in summer it is easier for consumers to adjust their electricity consumption in response to the changes in electricity pricing during the non summer time the estimated inelastic short run and long run income effects show that electricity is a necessity for consumers moreover the controversial electricity conservation policies are found to be ineffective measures for reducing electricity consumption in taiwan

the stochastic volatility in mean model empirical evidence from international stock markets in this paper we present an exact maximum likelihood treatment for the estimation of a stochastic volatility in mean svm model based on monte carlo simulation methods the svm model incorporates the unobserved volatility as an explanatory variable in the mean equation the same extension is developed elsewhere for autoregressive conditional heteroscedastic arch models known as the arch in mean arch m model the estimation of arch models is relatively easy compared with that of the stochastic volatility sv model however efficient monte carlo simulation methods for sv models have been developed to overcome some of these problems the details of modifications required for estimating the volatility in mean effect are presented in this paper together with a monte carlo study to investigate the finite sample properties of the svm estimators taking these developments of estimation methods into account we regard sv and svm models as practical alternatives to their arch counterparts and therefore it is of interest to study and compare the two classes of volatility models we present an empirical study of the intertemporal relationship between stock index returns and their volatility for the united kingdom the united states and japan this phenomenon has been discussed in the financial economic literature but has proved hard to find empirically we provide evidence of a negative but weak relationship between returns and contemporaneous volatility which is indirect evidence of a positive relation between the expected components of the return and the volatility process copyright 2002 john wiley sons ltd

lifeline electricity rates as an income transfer device the lifeline electricity rates are presumed to be inefficient because they violate optimal pricing principles but they may also be an ineffective and inequitable way to transfer assistance to low income households evidence is presented to challenge the assumption that simple demand changes will permit high consuming households to subsidize low income users social security food stamps and other social programs are better alternatives to a general income transfer 7 references 2 tables dck

a new stepwise power tariff model and its application for residential consumers in regulated electricity markets stepwise power tariff spt which has been put into practice is a crucial way for energy saving and environment protecting in this paper a new optimal model of spt based on residential demand response model is presented the optimal decision is proposed to restrain high electricity consumption as well as safeguard benefits of both supply and demand sides as a result the objective is designed to minimize electricity consumption and constraints are taken into consideration thoroughly including acceptable index of consumers average price sales profit of power providers and basic electricity demand which serves as a foundation for smooth implement of spt to solve the constrained optimal problem genetic algorithm ga is employed the effectiveness of the model and algorithm is investigated and demonstrated based on real data of 300 residents by a numerical example the study shows that the method can reduce power consumption obviously with little sacrifice of the benefits of consumers and power providers

measuring uncertainty and its impact on the economy we propose a new framework for measuring uncertainty and its effects on the economy based on a large var model with errors whose stochastic volatility is driven by two common unobservable factors representing aggregate macroeconomic and financial uncertainty the uncertainty measures can also influence the levels of the variables so that contrary to most existing measures ours reflect changes in both the conditional mean and volatility of the variables and their impact on the economy can be assessed within the same framework moreover identification of the uncertainty shocks is simplified with respect to standard var based analysis in line with the favar approach and with heteroskedasticity based identification finally the model which is also applicable in other contexts is estimated with a new bayesian algorithm which is computationally efficient and allows for jointly modeling many variables while previous var models with stochastic volatility could only handle a handful of variables empirically we apply the method to estimate uncertainty and its effects using us data finding that there is indeed substantial commonality in uncertainty sizable effects of uncertainty on key macroeconomic and financial variables with responses in line with economic theory

a national micro data based model of residential electricity demand new evidence on seasonal variation building on earlier estimates of electricity demand the author estimates elasticities by month to determine differences between heating and cooling seasons he develops a three equation model of residential electricity demand that includes all the main components of economic theory the model generates seasonal elasticity estimates that generally support economic theory based on the model using a national current household data set monthly division the evidence indicates there is a seasonal pattern for price elasticity of demand while less pronounced there also appears to be seasonal patterns for cross price elasticity of alternative fuels for the elasticity of appliance stock index and for an intensity of use variable

domestic fuel expenditure an analysis of three national surveys abstract this paper analyses the fuel expenditure data in three surveys looking particularly at the importance of household income multivariate data analysis techniques show that household size the size and type of accomodation and the presence of central heating are more direct influences on fuel expenditure than income changes in income have little independent effect on fuel expenditure once the size of the house size of household and heating system are determined

seasonal variation in residential electricity demand evidence from survey data in this paper we estimate twelve monthly electricity demand equations for households using a detailed microdata set the microdata are based largely on a detailed 1975 survey of us households and incude variables enabling us to measure block price schedules family income socio demographic variables appliance stocks housing characteristics and heating and cooling degree days of single family units we find that price elasticities are higher in absolute value during peak periods of demand income elasticity estimates show no discernible seasonal pattern our disaggregated data also allow us to estimate the seasonal usage patterns of several electricity using appliances the estimates follow expected patterns

revenue management with limited demand information in this paper we consider the classical multifare single resource leg problem in revenue management for the case where demand information is limited our approach employs a competitive analysis which guarantees a certain performance level under all possible demand scenarios the only information required about the demand for each fare class is lower and upper bounds we consider both competitive ratio and absolute regret performance criteria for both performance criteria we derive the best possible static policies which employ booking limits that remain constant throughout the booking horizon the optimal policies have the form of nested booking limits dynamic policies which employ booking limits that may be adjusted at any time based on the history of bookings are also obtained we provide extensive computational experiments and compare our methods to existing ones the results of the experiments demonstrate the effectiveness of these new robust methods

technology shocks in the new keynesian model in the new keynesian model preference cost push and monetary shocks all compete with the real business cycle model s technology shock in driving aggregate fluctuations a version of this model estimated via maximum likelihood points to these other shocks as being more important for explaining the behavior of output inflation and interest rates in the postwar u s data these results weaken the links between the current generation of new keynesian models and the real business cycle models from which they were originally derived they also suggest that federal reserve officials have often faced difficult trade offs in conducting monetary policy

the impact of the volatility of monetary policy shocks this paper studies the impact of the volatility of monetary policy using a structural vector auroregression svar model enriched along two dimensions first it allows for time varying variance of monetary policy shocks via a stochastic volatility specification second it allows a dynamic interaction between the level of the endogenous variables in the var and the time varying volatility the analysis establishes that the nominal interest rate output growth and inflation fall in reaction to an increase in the volatility of monetary policy the analysis also develops a dynamic stochastic general equilibrium model enriched with stochastic volatility to monetary policy that generates similar responses and provides a theoretical underpinning of these findings

the stochastic volatility in mean model with time varying parameters an application to inflation modeling this article generalizes the popular stochastic volatility in mean model to allow for time varying parameters in the conditional mean the estimation of this extension is nontrival since the volatility appears in both the conditional mean and the conditional variance and its coefficient in the former is time varying we develop an efficient markov chain monte carlo algorithm based on band and sparse matrix algorithms instead of the kalman filter to estimate this more general variant the methodology is illustrated with an application that involves u s u k and germany inflation the estimation results show substantial time variation in the coefficient associated with the volatility highlighting the empirical relevance of the proposed extension moreover in a pseudo out of sample forecasting exercise the proposed variant also forecasts better than various standard benchmarks

energy demand with declining rate schedules an econometric model for the u s commercial sector we specify and estimate a model of the demand for electricity and natural gas in commercial buildings using data from the commercial building energy consumption survey although not observed declining rate schedules are approximated by a downward sloping function fitted to billing data for individual survey units marginal prices rates temperature variables and a large number of building characteristics are incorporated into the model as explanatory variables demand and rate schedule equations constitute a simultaneous system with prices and quantities jointly determined the effects on price elasticities of using endogenous marginal rather than exogenous average prices are estimated to be quite large

electricity demand in multi family renter occupied residences this paper focuses on multi family renter occupied housing where the landlord provides major appliances a large residential sector that has not received widespread attention in the literature experimental data are used from a test where one group of households was billed directly for the electricity they consumed while a control group had unlimited electric service included as part of the monthly rent the empirical analysis yields short run demand estimates that satisfy to a remarkable extent the ceteris paribus assumptions of demand analysis this is the case for two reasons 1 the households did not individually execute the appliance choice decision at various unknown times in the past and 2 the stock of appliances upon which the derived short run demand is conditional is identical for all households in the sample a second important feature is emphasis on functional form examined in some detail is the question of the appropriate functional form for residential electricity demand finally empirical results of the analysis are used to investigate the cost effectiveness and welfare effects of installing submeters in existing multi family residences

long memory economic policy uncertainty and forecasting us inflation a bayesian varfima approach abstractwe compare inflation forecasts of a vector autoregressive fractionally integrated moving average varfima model against standard forecasting models u s inflation forecasts improve when controlling for persistence and economic policy uncertainty epu importantly the varfima model comprising of inflation and epu outperforms commonly used inflation forecast models

robust portfolio choice with learning in the framework of regret single period case in this paper we formulate a single period portfolio choice problem with parameter uncertainty in the framework of relative regret relative regret evaluates a portfolio by comparing its return to a family of benchmarks where the benchmarks are the wealths of fictitious investors who invest optimally given knowledge of the model parameters and is a natural objective when there is concern about parameter uncertainty or model ambiguity the optimal relative regret portfolio is the one that performs well in relation to all the benchmarks over the family of possible parameter values we analyze this problem using convex duality and show that it is equivalent to a bayesian problem where the lagrange multipliers play the role of the prior distribution and the learning model involves bayesian updating of these lagrange multipliers prior this bayesian problem is unusual in that the prior distribution is endogenously chosen by solving the dual optimization problem for the lagrange multipliers and the objective function involves the family of benchmarks from the relative regret problem these results show that regret is a natural means by which robust decision making and learning can be combined this paper was accepted by dimitris bertsimas optimization

residential energy use abstract the energy information administration recently published data they collected from the national interim energy consumption survey niecs niecs includes detailed information on 4081 individual households demographic characteristics energy related features of the structure heating equipment and appliances therein recent conservation actions taken by the household and fuel consumption and costs for the april 1978 march 1979 one year period this data set provides a new and valuable resource for analysis we summarized and analysed the niecs data on household energy consumption total energy use electricity use and use of the primary space heating fuel the regression equations constructed explain roughly half the variation in energy use among households these equations contain 10 or fewer independent variables the most important of which are fuel price year house was built floor area and heating degree days

appliance specific electricity consumption in slovene households abstract on the basis of a national household survey carried out in 1983 this study presents estimates of electricity use per appliance our estimates of electricity use for space heating water heating and cooking are considerably lower than the engineering estimates the estimates for other electricity using appliances broadly conform with engineering estimates our low estimate of the short run income elasticity is in close agreement with other studies

the short run residential demand for electricity the model of short run residential demand for electricity combines price schedule information obtained from the federal energy regulatory commission with household specific data from the 1972 73 consumer expenditure survey to determine the household s level of electricity consumption and relate it to the household s demographic profile and appliance stock the overall short run price elasticity estimate of 0 550 supports existing findings that short run residential electricity demand is price inelastic however the variation in elasticities across end use categories suggests that the overall response is made up of a complex set of responses that vary substantially and significantly across appliances this implies that it may be more efficient to tailor conservation policies to the stock configuration of the population 17 references 6 tables

lifeline electricity rates as an income transfer device comment the authors question the supporting evidence given in an earlier paper by burgess and paglin eapa 7 4039 they suggest using the national interim energy consumption survey niecs as an alternative base and present a new set of equations to validate the income elasticity of demand in the justification of lifeline rates burgess and paglin reply noting that garbacz s study raises questions about a national requirement for lifeline rates 4 references 5 tables dck

residential demand for fuelwood this is the first national microbased study of residential demand for wood as fuel the data are from the us department of energy residential energy consumption survey the model employs a somewhat unique interaction dummy for price that allows the simultaneity problem to be adjusted for in a 2sls format and then the interaction term to be calculated and entered in the second stage results are compared with elasticity estimates derived from the same data set for the four other main residential fuels wood has a price elasticity of 0 421 for main users

residential energy demand additional empirical evidence by minority household type abstract in a number of recent studies household level data for specific urban areas or national household level micro data have been used to estimate price and income elasticities of energy demand none of this literature however provides us with elasticity estimates by minority majority household type the main focus of this paper is to measure the responsiveness of the quantity of electricity and total energy demanded for black hispanis and majority households to price and income price and income elasticities are compared among these groups over the short and long term a variable elasticity demand model is estimated the elasticities are allowed to vary with respect to non price and income variables the price elasticities of demand vary with heating and cooling degree days and the income elasticities with the number of household members mean estimates were calculated over the respective samples findings indicate that demand for electricity is relatively price inelastic irrespective of household group however blacks are more sensitive to variations in the short run to price than hispanic and majority households in the long run blacks are also more sensitive to price changes but the magnitude of the response to price changes in the long run relative to the short run is larger for hispanics and majority households respectively than for blacks

residential demand for electricity under inverted block rates evidence from a controlled experiment block rate structures are used extensively in public utility pricing including residential electricity estimating price elasticities in this context is complicated by the resulting nonlinearity of the consumer s budget constraint this article estimates the demand for electricity under inverted block rates using data from a residential rate experiment the study provides an opportunity to obtain short run price elasticities in an experimental setting and to compare alternative estimators developed for nonlinear budget constraints elasticities of demand with respect to individual components of the block rate are developed using a modification of the structural maximum likelihood estimator

is there an effect of policy related uncertainty on inflation evidence from the united states under trump this study bridges the existing literature on the macroeconomic effects of policy related uncertainty and the literature on inflation dynamics and provide fresh insights on the impacts of policy re

an engineering econometric analysis of seasonal energy demand and conservation in the pacific northwest this article estimates a new model of residential electricity demand it differs from previous work in two ways first we use individual monthly billing data in a pooled time series cross section framework second we use an engineering thermal load technique to model the household space heating technology we estimate the model using data from the pacific northwest and use the results to analyze three conservation measures a price increase a reduction in thermostat settings and improvement of insulation levels we find average rates of return for insulation upgrades of 4 9 for ceilings and 8 3 for walls

a new approach to identifying the real effects of uncertainty shocks this article introduces the use of the sign restrictions methodology to identify uncertainty shocks we apply our methodology to a class of vector autoregression models with stochastic volatility t

short run residential demand for fuels a disaggregated approach a disaggregated model of residential energy demand is specified and then used to examine the data and econometric techniques available to estimate such a model inconsistencies in the currently popular random effects model and weighted least squares generate inconsistent parameter estimates for short run modeling some of the currently available pooled data is of poor quality the principal data series of concern are the appliance stock series but current research is attempting to improve aggregate data while the disaggregated elasticities reported can only be considered tentative the approach combined with better data and econometric techniques will produce an important policy tool the regression results are summarized in two tables in the appendix 42 references 5 tables

revenue management without forecasting or optimization an adaptive algorithm for determining airline seat protection levels we investigate a simple adaptive approach to optimizing seat protection levels in airline revenue management systems the approach uses only historical observations of the relative frequencies of certain seat filling events to guide direct adjustments of the seat protection levels in accordance with the optimality conditions of brumelle and mcgill 1993 stochastic approximation theory is used to prove the convergence of this adaptive algorithm to the optimal protection levels in a simulation study we compare the revenue performance of this adaptive approach to a more traditional method that combines a censored forecasting method with a common seat allocation heuristic emsr b

is there an interest rate speculation relationship evidence from g7 in the pre and post 2008 crisis abstractthe article revisits the is lm macroeconomic model by incorporating speculation into the investment function the discussion is supported empirically by using data from the g7 countries to examine the different interest rate regimes in the pre and post 2008 financial crisis the estimation of an anchor interest rate provides a reference rate for the g7 countries the empirical study is extended to examine if the three quantitative easing qe episodes in the u s are growth promoting the article concludes that the maintenance of a high and stable interest rate policy is needed for sustainable growth in the g7 countries

were there regime switches in u s monetary policy working paper 2004 14 june 2004 abstract a multivariate model identifying monetary policy and allowing for simultaneity and regime switching in coefficients and variances is confronted with u s data since 1959 the best fit is with a model that allows time variation in structural disturbance variances only among models that also allow for changes in equation coefficients the best fit is for a model that allows coefficients to change only in the monetary policy rule that model allows switching among three main regimes and one rarely and briefly occurring regime the three main regimes correspond roughly to periods when most observers believe that monetary policy actually differed and the differences in policy behavior are substantively interesting though statistically ill determined the estimates imply monetary targeting was central in the early 80s but was also important sporadically in the 70s the changes in regime were essential neither to the rise in inflation in the 70s nor to its decline in the 80s jel classification e52 e47 c53 key words counterfactuals lucas critique policy rule monetary targeting simultaneity volatility model comparison i the debate over monetary policy change in an influential paper clarida gali and gertler 2000 cgg presented evidence that us monetary policy changed between the 1970 s and the 1980 s indeed that in the 70 s it was drastically worse they found that the policy rule apparently followed in the 70 s was one that when embedded in most stochastic general equilibrium models would imply non uniqueness of the equilibrium and hence vulnerability of the economy to sunspot fluctuations of arbitrarily large size their estimated policy rule for the later period on the other hand eliminated this indeterminacy these results are a possible explanation of the volatile and rising inflation of the 70 s and of its subsequent decline the cgg analysis has two important weaknesses one is that it fails to account for stochastic volatility us macroeconomic variables and particularly the federal funds rate have gone through periods of tranquility and of agitation with forecast error variances varying greatly from period to period ignoring such variation does not lead to inconsistent estimates of model parameters when the forecasting equations themselves are constant but it strongly biases toward a finding of changed parameters tests of the stability of the forecasting equations the other weakness is that the cgg analysis rests on powerful and implausible identifying assumptions they require that we accept that the response of the monetary authority to expected future inflation and output does not depend on the recent history of inflation money growth or output it is hard to understand why this should be so especially in the 70 s when monetarism was a prominent theme in policy debates congress was requiring reports from the fed of projected time paths of monetary aggregates and financial markets were reacting sensitively to weekly money supply numbers the requirement for existence and uniqueness of equilibrium in dynamic models is that the monetary policy rule show a more than unit response of interest rates to the sum of the logs of all nominal variables that appear on the right hand side of the reaction function if we force a particular measure of expected future inflation to proxy for all the nominal variables that actually appear independently in the reaction function we are bound to get distorted conclusions on the one hand because expected future inflation will be a noisy measure of the full set of nominal influences on policy we might get downward bias in our estimates from the usual errorsin variables effect on the other hand to the extent that expected future inflation like most expected future values shows less variation than current nominal variables we could find a mistaken scaling up of coefficients

two illustrations of the quantity theory of money breakdowns and revivals by extending his data we document the instability of low frequency regression coefficients that lucas 1980 used to express the quantity theory of money we impute the differences in these regression coefficients to differences in monetary policies across periods a dsge model estimated over a subsample like lucas s implies values of the regression coefficients that confirm lucas s results for his sample period but perturbing monetary policy rule parameters away from the values estimated over lucas s subsample alters the regression coefficients in ways that reproduce their instability over our longer sample jel c51 e23 e31 e43 e51 e52 robert e lucas jr 1980 used near unit slopes of univariate regressions of moving averages of inflation and interest rates on money growth for the united states for the period 1953 1977 to illustrate two central implications of the quantity theory of money that a given change in the rate of change in the quantity of money induces i an equal change in the rate of price inflation and ii an equal change in nominal rates of interest lucas said that those two quantity theoretic propositions

consumer responses to time varying prices for electricity abstract we report new experimental evidence of the household response to weekday differentials in peak and off peak electricity prices the data come from auckland new zealand where peak residential electricity consumption occurs in winter for heating peak off peak price differentials ranged over four randomly selected groups from 1 0 to 3 5 on average there was no response except in winter in winter participant households reduced electricity consumption by at least 10 took advantage of lower off peak prices but did not respond to the peak price differentials response varied with house and household size time spent away from home and whether water was heated with electricity

residential demand for liquid petroleum gas abstract this is the first micro based study of residential demand for liquid petroleum gas lpg the data are from doe s residential energy consumption survey results are compared with elasticity estimates derived from the same data set for the three other main residential fuels lpg has a price elasticity for space and water heating combined of 1 3 income elasticity is 0 207

optimal departures from marginal cost pricing focuses on departures from marginal cost pricing optimal allocation or resources level of tax revenue that will be collected by the government theorems developed for resource allocation ebsco

monetary policy uncertainty and economic fluctuations uncertainty associated with the monetary policy transmission mechanism is a key driving force of business cycles to investigate this link we propose a new term structure model that allows the volatility of the yield curve to interact with macroeconomic indicators the data favors a model with two volatility factors that capture shortterm and long term monetary policy uncertainty increases in either of them lead higher unemployment rates but they interact with ination in opposite directions

two illustrations of the quantity theory of money of two central implications of the quantity theory of money that a given change in the rate of change in the quantity of money induces i an equal change in the rate of price inflation and ii an equal change in nominal rates of interest the illustrations were obtained by comparing moving averages of the three variables in question using quarterly u s time series for the period 1953 77 readers may find the results of interest as additional confirmation of the quantity theory as an example of one way in which the quantity theoretic relationships can be uncovered via atheoretical methods from time series which are subject to a variety of other forces or as a measure of the extent to which the inflation and interest rate experience of the postwar period can be understood in terms of purely classical monetary forces the theoretical background of the study is reviewed very briefly as it is familiar material in the next section the data processing methods are described and rationalized in section ii the illustrations

the demand for electricity and natural gas in the northeastern united states the demand for natural gas and electricity for the residential commercial and industrial sectors was estimated using a combination of the error components model and seemingly unrelated regressions the estimated demand models showed both natural gas and electricity to be price elastic in the long run and price inelastic in the short run in all sectors except the commercial sector in which electricity demand is unresponsive to its own price natural gas had negligible income elasticities in the residential and commercial sectors and a long run income elasticity of 2 86 in the industrial sector electricity had an insignificant income effect in all sectors but the industrial where its long run elasticity was unitary only in the residential demand for natural gas is the cross price elasticity substantial with the price of electricity having a long run cross elasticity of 1 70 fuel oil prices generally had a negative impact probably indicating a large income effect the elasticities of adjustment were higher for natural gas than electricity indicating a faster adjustment to change either in response to greater instability in energy availability or reflecting more alternative fuels or both 16 references 4 tables