nep-ets New Economics Papers
on Econometric Time Series
Issue of 2018‒08‒13
twenty-one papers chosen by
Jaqueson K. Galimberti
KOF Swiss Economic Institute

  1. Granger causality testing in mixed-frequency Vars with possibly (co)integrated processes By Hecq, Alain; Goetz, Thomas
  2. Bootstrapping Impulse Responses of Structural Vector Autoregressive Models Identified through GARCH By Helmut Lütkepohl; Thore Schlaak
  3. Testing of Binary Regime Switching Models using Squeeze Duration Analysis By Milan Kumar Das; Anindya Goswami
  4. Identification with external instruments in structural VARs under partial invertibility By Silvia Miranda Agrippino; Giovanni Ricco
  5. The likelihood of effective lower bound events By Michal Franta
  6. The Forcasting Performance of Dynamic Factor Models with Vintage Data By Di Bonaventura, Luca; Forni, Mario; Pattarin, Francesco
  7. Does time-variation matter in the stochastic volatility components for G7 stock returns By Afees A. Salisu; Ahamuefula Ephraim Ogbonna
  8. Entropy Analysis of Financial Time Series By Stephan Schwill
  9. Asymmetry and Multiscale Dynamics in Macroeconomic Time Series Analysis By Habimana, Olivier
  10. UK regional nowcasting using a mixed frequency vector autoregressive model By Gary Koop; Stuart McIntyre; James Mitchell
  11. The Impact of Exchange Rate Dynamics on Agricultural Output Performance in Nigeria By Adekunle, Wasiu; Ndukwe, Innocent
  12. Electricity Consumption, Economic Growth and Trade Openness in Kazakhstan: Evidence from Cointegration and Causality By Khan, Saleheen; Jam, Farooq Ahmed; Shahbaz, Muhammad; Mamun, Md Al
  13. Fitting Okun's law for the Swazi Kingdom: Will a nonlinear specification do? By Andrew Phiri
  14. Time-Varying Impact of Geopolitical Risks on Oil Prices By Juncal Cunado; Rangan Gupta; Chi Keung Marco Lau; Xin Sheng
  15. Is the relationship between financial development and income inequality symmetric or asymmetric ? new evidence from South Africa based on NARDL By Haffejee, muhammad Ismail; Masih, Mansur
  16. Exchange Rate Pass-through to Domestic Prices in Thailand, 2000-2017 By Jiranyakul, Komain
  17. Analysis of shock transmissions to a small open emerging economy using a SVARMA model By Raghavan, Mala; Athanasopoulos, George
  18. Do both demand-following and supply-leading theories hold true in developing countries? By Chow, Sheung Chi; Vieito, João Paulo; Wong, Wing-Keung
  19. Uncertainty and Volatility Jumps in the Pound-Dollar Exchange Rate: Evidence from Over One Century of Data By Konstantinos Gkillas; Rangan Gupta; Dimitrios Vortelinos
  20. Explosive Dynamics in House Prices? An Exploration of Financial Market Spillovers in Housing Markets Around the World By Martinez-Garcia, Enrique; Grossman, Valerie
  21. Joint and conditional dependence modeling of peak district heating demand and outdoor temperature: a copula-based approach By F. Marta L. Di Lascio; Andrea Menapace; Maurizio Righetti

  1. By: Hecq, Alain; Goetz, Thomas
    Abstract: We analyze Granger causality testing in mixed-frequency VARs with possibly (co)integrated time series. It is well known that conducting inference on a set of parameters is dependent on knowing the correct (co)integration order of the processes involved. Corresponding tests are, however, known to often suffer from size distortions and/or a loss of power. Our approach, which boils down to the mixed-frequency analogue of the one by Toda and Yamamoto (1995) or Dolado and Lutkepohl (1996), works for variables that are stationary, integrated of an arbitrary order, or cointegrated. As it only requires an estimation of a mixed-frequency VAR in levels with appropriately adjusted lag length, after which Granger causality tests can be conducted using simple standard Wald test, it is of great practical appeal. We show that the presence of non-stationary and trivially cointegrated highfrequency regressors (Goetz et al., 2013) leads to standard distributions when testing for causality on a parameter subset, without any need to augment the VAR order. Monte Carlo simulations and two applications involving the oil price and consumer prices as well as GDP and industrial production in Germany illustrate our approach.
    Keywords: Mixed frequencies; Granger causality; Hypothesis testing, Vector autoregressions; Cointegration
    JEL: C32
    Date: 2018–06–27
  2. By: Helmut Lütkepohl; Thore Schlaak
    Abstract: Different bootstrap methods and estimation techniques for inference for structural vector autoregressive (SVAR) models identified by conditional heteroskedasticity are reviewed and compared in a Monte Carlo study. The model is a SVAR model with generalized autoregressive conditional heteroskedastic (GARCH) innovations. The bootstrap methods considered are a wild bootstrap, a moving blocks bootstrap and a GARCH residual based bootstrap. Estimation is done by Gaussian maximum likelihood, a simplified procedure based on univariate GARCH estimations and a method that does not re-estimate the GARCH parameters in each bootstrap replication. It is found that the computationally most efficient method is competitive with the computationally more demanding methods and often leads to the smallest confidence sets without sacrificing coverage precision. An empirical model for assessing monetary policy in the U.S. is considered as an example. It is found that the different inference methods for impulse responses lead to qualitatively very similar results.
    Keywords: Structural vector autoregression, conditional heteroskedasticity, GARCH, identification via heteroskedasticity
    JEL: C32
    Date: 2018
  3. By: Milan Kumar Das; Anindya Goswami
    Abstract: We have developed a statistical technique to test the model assumption of binary regime switching extension of the geometric Brownian motion (GBM) model by proposing a new discriminating statistics. Given a time series data, we have identified an admissible class of the regime switching candidate models for the statistical inference. By performing several systematic experiments, we have successfully shown that the sampling distribution of the test statistics differs drastically, if the model assumption changes from GBM to Markov modulated GBM, or to semi-Markov modulated GBM. Furthermore, we have implemented this statistics for testing the regime switching hypothesis with Indian sectoral indices.
    Date: 2018–07
  4. By: Silvia Miranda Agrippino (Bank of England); Giovanni Ricco (Observatoire français des conjonctures économiques)
    Abstract: This paper discusses the conditions for indentification with external instruments in Structural VARs under partial invertibility. We observe that in this case the shocks of interest and their effects can be recovered using an external instrument, provided that a condition of limited lag exogeneity holds. This condition is weaker than that required for LP-IV, and allows for recoverability of impact effects also une VAR misspecification. We assess our claims in a simulated environment, and provide an emirical application to the relevant cas of identification of monetary policy shocks.
    Keywords: Identification with external instruments; Structural VAR; Invertibility; Monetary Policy Shocks
    JEL: C3 C32 E30 E52
    Date: 2018–07
  5. By: Michal Franta
    Abstract: This paper provides estimates of the probability of an economy hitting its effective lower bound (ELB) on the nominal interest rate and of the expected duration of such an event for eight advanced economies. To that end, a mean-adjusted panel vector autoregression with static interdependencies and the possibility of regime change is estimated. The simulation procedure produces ELB risk estimates for both the short term, where the current phase of the business cycle plays an important role, and the medium term, where the occurrence of an ELB situation is determined mainly by the equilibrium values of macroeconomic variables. The paper also discusses the ELB event probability estimates with respect to previous approaches used in the literature.
    Keywords: effective lower bound, ELB risk, mean adjustment, panel VAR, regime change
    JEL: E37 E52 C11
    Date: 2018–06
  6. By: Di Bonaventura, Luca; Forni, Mario; Pattarin, Francesco
    Abstract: We present a comparative analysis of the forecasting performance of two dynamic factor models, the Stock and Watson (2002a, b) model and the Forni, Hallin, Lippi and Reichlin (2005) model, based on vintage data. Our dataset contains 107 monthly US "first release" macroeconomic and financial vintage time series, spanning the 1996:12 to 2017:6 period with monthly periodicity, extracted from the Bloomberg database†. We compute real-time one-month-ahead forecasts with both models for four key macroeconomic variables: the month-on-month change in industrial production, the unemployment rate, the core consumer price index and the ISM Purchasing Managers' Index. First, we find that both the Stock and Watson and the Forni, Hallin, Lippi and Reichlin models outperform simple autoregressions for industrial production, unemployment rate and consumer prices, but that only the first model does so for the PMI. Second, we find that neither models always outperform the other. While Forni, Hallin, Lippi and Reichlin's beats Stock and Watson's in forecasting industrial production and consumer prices, the opposite happens for the unemployment rate and the PMI.
    Keywords: Dynamic factor models; First release data; Forecasting; Forecasting Performance; Vintage data
    JEL: C01 C32 C52 C53 E27 E37
    Date: 2018–07
  7. By: Afees A. Salisu (Department for Management of Science and Technology Development, Ton Duc Thang University, Ho Chi Minh City, Vietnam Faculty of Business Administration, Ton Duc Thang University, Ho Chi Minh City, Vietnam Centre for Econometric and Allied Research, University of Ibadan); Ahamuefula Ephraim Ogbonna (Centre for Econometric and Allied Research, University of Ibadan Department of Statistics, University of Ibadan, Ibadan, Nigeria)
    Abstract: This study empirically tests for time variation in the stochastic volatility (SV) components for the G7 stock returns. The time variation in both trend and transitory components of the SV is tested separately and jointly using the unobserved component model and following the approach developed by Chan (2018). Consequently, the computed Bayes factor obtained from the SavageDickey density ratio, which circumvents the computation of marginal likelihood, is used to adjudge the performance of each restricted time varying stochastic volatility model without the trend and transitory components against the unrestricted model that allows for same. The empirical evidence supports time variation in the transitory component of SV while the trend component is found to be relatively constant over time. These empirical estimates are not sensitive to data frequency.
    Keywords: Bayesian; Bayes factor; Transitory component; Trend component; Unobserved Component Model
    JEL: C11 C32 C53 E37 G17
    Date: 2018–07
  8. By: Stephan Schwill
    Abstract: This thesis applies entropy as a model independent measure to address three research questions concerning financial time series. In the first study we apply transfer entropy to drawdowns and drawups in foreign exchange rates, to study their correlation and cross correlation. When applied to daily and hourly EUR/USD and GBP/USD exchange rates, we find evidence of dependence among the largest draws (i.e. 5% and 95% quantiles), but not as strong as the correlation between the daily returns of the same pair of FX rates. In the second study we use state space models (Hidden Markov Models) of volatility to investigate volatility spill overs between exchange rates. Among the currency pairs, the co-movement of EUR/USD and CHF/USD volatility states show the strongest observed relationship. With the use of transfer entropy, we find evidence for information flows between the volatility state series of AUD, CAD and BRL. The third study uses the entropy of S&P realised volatility in detecting changes of volatility regime in order to re-examine the theme of market volatility timing of hedge funds. A one-factor model is used, conditioned on information about the entropy of market volatility, to measure the dynamic of hedge funds equity exposure. On a cross section of around 2500 hedge funds with a focus on the US equity markets we find that, over the period from 2000 to 2014, hedge funds adjust their exposure dynamically in response to changes in volatility regime. This adds to the literature on the volatility timing behaviour of hedge fund manager, but using entropy as a model independent measure of volatility regime.
    Date: 2018–07
  9. By: Habimana, Olivier
    Abstract: This thesis consists of three independent articles preceded by an introductory chapter. The first two articles focus on exchange rate dynamics in emerging market and developing economies, taking into account nonlinearities and asymmetries which are relevant for these countries and are potentially due to (i) transaction costs and other market frictions, and (ii) official intervention in the foreign exchange market. The third article is devoted to the analysis of the effects of monetary policy at different time horizons. The first article evaluates the purchasing power parity (PPP) theory in a panel of Sub-Saharan African countries. Unit root tests that are based on exponential smooth transition autoregressive (ESTAR) models are applied to account for nonlinearities and asymmetries in real exchange rate adjustment towards its equilibrium (mean) value. The results indicate empirical support for the PPP theory. The second article examines the relationship between current account adjustment and exchange rate flexibility in a panel of emerging market and developing economies. The purpose of this article is to (i) obtain a measure of exchange rate flexibility that considers autoregressive conditional heteroscedasticity and possible asymmetric responses of the exchange rate to shocks, and (ii) apply suitable dynamic panel data estimators to investigate this relationship. The results indicate that more flexible exchange rates are associated with faster current account adjustment. By means of wavelets the third article investigates the liquidity effect and the long-run neutrality of money at detailed timescales using time series data for Sweden and the US. The results indicate a significant liquidity effect at horizons of one to four years, but there is no evidence of monetary neutrality.
    Keywords: asymmetry, multiscale, time series, wavelets
    JEL: C15 C22 C23 E52 E6 F41 G1
    Date: 2018–06–19
  10. By: Gary Koop (University of Strathclyde); Stuart McIntyre (University of Strathclyde); James Mitchell (University of Warwick)
    Abstract: Data on Gross Value Added (GVA) are currently only available at the annual frequency for the UK regions and are released with significant delay. Regional policymakers would benefit from more frequent and timely data. The goal of this paper is to provide these. We use a mixed frequency Vector Autoregression (VAR) to provide, each quarter, nowcasts (i.e. forecasts of current GVA which is as yet unknown due to release delays) of annual GVA growth for the UK regions. The information we use to update our regional nowcasts comes from GVA growth for the UK as a whole as this is released in a more timely and frequent (quarterly) fashion. To improve our nowcasts we use entropic tilting methods to exploit the restriction that UK GVA growth is a weighted average of GVA growth for the UK regions. In this paper, we develop the econometric methodology and test it in the context of a real time nowcasting exercise.
    Keywords: Regional growth, nowcasting, mixed frequency
    JEL: C22 C52 C53 E01 R1
    Date: 2018–07
  11. By: Adekunle, Wasiu; Ndukwe, Innocent
    Abstract: Abstract The study investigated the possible asymmetric effect of real exchange rate dynamics on agricultural output performance in Nigeria over the period of 1981 to 2016 by collecting data from secondary sources. The study employed a combination of stationary and nonstationary variables as was found out through the ADF unit root test. Based on the Bounds test for cointegration, a long-run relationship was absent between real exchange rate and agricultural output, irrespective of specifications. Generally, the result of model estimation showed that the significant drivers of agricultural output are real exchange rate (log-levels), real appreciation and depreciation (after some lags), industrial capacity utilization rate, and government expenditure on agriculture (after some lags). ACGSF loan exerted positive and insignificant influence on agricultural output. In addition, though the effect of real appreciation was larger than that of real depreciation, the present study could not find any evidence in support of the asymmetric effect of real exchange rate dynamics on agricultural output performance in the Nigerian economy. It is therefore suggested that fiscal and monetary authorities in Nigeria should work in unison at ensuring that the full potentials of the agricultural sector are harnessed for the growth and development of the country.
    Keywords: Keywords: Real exchange rate, Agricultural output, and Asymmetry
    JEL: Q1 Q17 Q18 Q19
    Date: 2018–06–02
  12. By: Khan, Saleheen; Jam, Farooq Ahmed; Shahbaz, Muhammad; Mamun, Md Al
    Abstract: We investigate the relation between electricity consumption and economic growth by incorporating trade openness, capital, and labor in production function of Kazakhstan using annual data for 1991-2014. We apply the ARDL bounds testing and the VECM Granger causality approach to examine long run and causality relation between the variables. Our results confirm the existence of long run relation among the series. The empirical evidence reveals that electricity consumption adds in economic growth. Trade openness stimulates economic growth, and capital and labor promote economic growth, as well. The causality analysis shows that electricity consumption Granger causes economic growth and trade openness. We also document feedback effect between trade openness and economic growth. Our study provides new insights for policy makers to articulate a comprehensive economic, trade and energy policy to sustain long run economic growth in Kazakhstan.
    Keywords: Electricity, Economic growth, Kazakhstan, VECM
    JEL: A10
    Date: 2018–07–01
  13. By: Andrew Phiri (Department of Economics, Nelson Mandela University)
    Abstract: Despite Okun’s law being hailed one of the most fundamental pieces within macroeconomic policy paradigm, empirical evidence existing for the Kingdom of Swaziland remains virtually non-existent. Our study fills this void/hiatus in the literature by examining Okun’s law for the Swazi Kingdom by using the nonlinear autoregressive distributive lag (N-ARDL) model applied to data collected over 1991 to 2017. To ensure robustness of our empirical analysis, we further apply the Corbae-Oularis (C-O) filter to extract the gap variables required for empirical estimates. Remarkably, we find strong evidence for nonlinear Okun’s trade-off between unemployment and output growth in Swaziland with this trade-off being stronger during recessionary periods compared to expansionary periods. Much-needed policy enlightenment is drawn for Swazi authorities from our findings.
    Keywords: Okun’s law, Nonlinear autoregressive distributive lag (N-ARDL) model, Swaziland, Sub-Saharan African (SSA) country, Corbae-Oularis filter.
    JEL: C22 C32 E24 O40
    Date: 2018–08
  14. By: Juncal Cunado (University of Navarra, School of Economics, Pamplona, Spain); Rangan Gupta (Department of Economics, University of Pretoria, Pretoria, South Africa); Chi Keung Marco Lau (Huddersfield Business School, University of Huddersfield, Huddersfield, United Kingdom); Xin Sheng (Huddersfield Business School, University of Huddersfield, Huddersfield, United Kingdom)
    Abstract: This paper analyses the dynamic impact of geopolitical risks (GPRs) on real oil returns for the period February 1974 to August 2017, using a time-varying parameter structural vector autoregressive (TVP-SVAR) model. Besides the two variables of concern, the model also includes growth in world oil production, global economic activity (to capture oil-demand), and world stock returns. We show that GPRs (based on a tally of newspaper articles covering geopolitical tensions), in general, has a significant negative impact on oil returns, primarily due to the decline in oil demand captured by the global economic activity. Our results, thus, highlight the risk of associating all GPRs with oil supply shocks driven by geopolitical tensions in the Middle East, and hence, ending up suggesting that higher GPRs drive up oil prices.
    Keywords: Oil markets, geopolitical risks, time-varying parameter structural vector autoregressive (TVP-SVAR) model
    JEL: C32 Q43
    Date: 2018–07
  15. By: Haffejee, muhammad Ismail; Masih, Mansur
    Abstract: Income inequality in South Africa has been increasing from a Gini-coefficient height of 0.57 in 2000 to 0.65 in 2014. It is therefore important to investigate whether, in a developing economy, financial sector development reduces or worsens income inequality by mobilising and allocating savings into productive investments. For this purpose, South Africa, with arguably the second-largest economy in Africa, has been identified. The Non-linear Auto Regressive Distributed Lag (NARDL) technique advanced by Shin et. al. (2014) has been applied. This paper contributes to existing literature both in terms of being country-specific as well as demonstrating for the first time, to the best of our knowledge, that there is no long-run asymmetry between financial development and income inequality. Our conclusions support the pressing need for double-digit economic growth in South Africa together with moderate increase in government consumption expenditures.
    Keywords: Financial development, Income Inequality, South Africa, NARDL
    JEL: C22 C58 G23
    Date: 2018–06–12
  16. By: Jiranyakul, Komain
    Abstract: This paper explores the degree of exchange rate pass-through to domestic prices in Thailand using quarterly data from 2000Q1 to 2017Q4. Johansen cointegration tests are employed in the analysis. The degree of exchange rate pass-through is found to be partial and modest. The stable pass-through effect in the long-run is found for import price index. The findings give some implications for risk perception by firms and investors regarding the future inflationary environment of the country.
    Keywords: Exchange rate, domestic prices, cointegration
    JEL: C22 E31 F31
    Date: 2018–06
  17. By: Raghavan, Mala (Tasmanian School of Business & Economics, University of Tasmania); Athanasopoulos, George (Monash University)
    Abstract: Using a parsimonious structural vector autoregressive moving average (SVARMA) model, we analyse the transmission of foreign and domestic shocks to a small open emerging economy under di erent policy regimes. Narrower con dence bands around the SVARMA responses compared to the SVAR responses, advocate the suitability of this framework for analysing the propagation of economic shocks over time. Malaysia is an interesting small open economy that has experienced an ongoing process of economic transition and development. The Malaysian government imposed exchange rate and capital control measures following the 1997 Asian nancial crisis. Historical and variance decompositions highlight Malaysia's high exposure to foreign shocks. The effects of these shocks change over time under di erent policy regimes. During the pegged exchange rate period, Malaysian monetary policymakers experienced some breathing space to focus on maintaining price and output stability. In the post-pegged period, Malaysia's exposure to foreign shocks increased and in recent times are largely driven by world commodity price and global activity shocks.
    Keywords: SVARMA models, Open Economy Macroeconomics, ASEAN, Shock transmissions
    JEL: C32 F41 E52
    Date: 2018
  18. By: Chow, Sheung Chi; Vieito, João Paulo; Wong, Wing-Keung
    Abstract: To overcome the limitations of the traditional approach which uses linear causality to examine whether the supply-leading and demand-following theories hold. As certain countries will be found not to follow the theory by using the traditional approach, this paper first suggests using all the proxies of financial development and economic growth as well as both multivariate and bivariate linear and nonlinear causality tests to analyze the relationship between financial development and economic growth. The multivariate nonlinear test not only takes into consideration both dependent and joint effects among variables, but is also able to detect a multivariate nonlinear deterministic process that cannot be detected by using any linear causality test. We find five more countries in which the supply-leading hypothesis and/or demand-following hypothesis hold true than with the traditional approach. However, there is still one country, Pakistan, for which no linear or nonlinear causality is found between its financial development and economic growth. To overcome this limitation, this paper suggests including cointegration in the analysis. This leads us to conclude that either supply-leading or demand-following hypotheses or both hold for all countries without any exception. There will be some types of relationships between economic growth and financial development in any country such that either they move together or economic growth causes financial development or financial development causes economic growth without any exception. The finding in our paper is may be useful for governments, politicians, and other international institutions in their decision making process for the development of the countries and reducing poverty.
    Keywords: Financial development, economic growth, cointegration, linear causality, nonlinear causality, developing countries, supply-leading hypothesis, demand-following theory.
    JEL: C12 F20 O40
    Date: 2018–06–26
  19. By: Konstantinos Gkillas (Department of Business Administration, University of Patras, Patras, Greece); Rangan Gupta (Department of Economics, University of Pretoria, Pretoria, South Africa); Dimitrios Vortelinos (Lincoln Business School, University of Lincoln, Lincoln, UK)
    Abstract: In this paper, we analyse the role of economic uncertainty, in predicting volatility jumps in the pound-dollar exchange rate over the monthly period of 1900:02 to 2018:05, with the jumps computed using daily data over the same period. Standard linear Granger causality test fail to detect any evidence of uncertainty causing volatility jumps. But given strong evidence of nonlinearity and structural breaks between jumps and economic uncertainty, we next use a nonparametric causality-in-quantiles test, given the misspecification of the linear model. Using this data-driven robust approach, we detect overwhelming evidence of uncertainty causing volatility jumps of the dollar-pound exchange rate over its entire conditional distribution, with the strongest effect observed at the lowest considered conditional quantile. In addition, our results are, in general, found to be robust to alternative measures of uncertainty, jumps generated at daily frequency based on shorter-samples of intraday data, and across three other dollar-based exchange rates.
    Keywords: Exchange Rates, Volatility Jumps, Uncertainty
    JEL: C22 F31
    Date: 2018–07
  20. By: Martinez-Garcia, Enrique (Federal Reserve Bank of Dallas); Grossman, Valerie (Federal Reserve Bank of Dallas)
    Abstract: Asset prices in general, and real house prices in particular, are often characterized by a nonlinear data-generating process which displays mildly explosive behavior in some periods. Here, we investigate the effect of asset market spillovers on the emergence of explosiveness in the dynamics of real house prices. The recursive unit root test of Phillips et al. (2015a, b) detects and date-stamps statistically-significant periods of mildly explosive behavior. With that methodology, we establish a timeline of periodically-collapsing episodes of explosiveness for a panel of 23 countries from the Federal Reserve Bank of Dallas’ International House Price Database (Mack and Martínez-García (2011)) between first quarter 1975 and fourth quarter 2015. Motivated by the theoretical notion of financial spillovers, we examine within a dynamic panel logit framework whether macro fundamentals—and, more specifically, financial variables—help predict episodes of explosiveness. Spreads in yields and real stock market growth together with standard macro variables (growth in personal disposable income per capita and inflation) are found empirically to be among the best predictors. We therefore conclude that financial developments in other asset markets play a significant role in the emergence of explosiveness in real house prices.
    Keywords: Financial Spillovers; Mildly Explosive Time Series; Right-Tailed Unit-Root Tests; Dynamic Panel Logit Model; International Housing Markets
    JEL: C22 G12 R30 R31
    Date: 2018–07–01
  21. By: F. Marta L. Di Lascio (Free University of Bolzano‐Bozen, Faculty of Economics, Italy); Andrea Menapace (Free University of Bolzano‐Bozen, Faculty of Science and Technology, Italy); Maurizio Righetti (Free University of Bolzano‐Bozen, Faculty of Science and Technology, Italy)
    Abstract: This paper examines the complex dependence between the peak district heating demand and the outdoor temperature. The final aim is to provide the probability law of the heat demand given extreme weather conditions and derive useful implications for the management and the production of thermal energy. We propose a copula-based approach and consider the case of the district of the city of Bozen-Bolzano. The analysed data concerns daily maxima of heat demand observed from January 2014 to November 2017 and the corresponding outdoor temperature. We find that the marginal behavior of the univariate time series of the district heating demand and the temperature is well-described by autoregressive integrated moving average models. Moreover, the selected copula model exhibits a symmetric dependence between the two investigated phenomena that tend to comove closely together during the whole heating season. Taking into account the conditional behaviour of the heat demand given the temperature leads to find that the demand is strongly affected by the temperature and, in case of extreme climatic events, the demand of thermal energy reach a peak with high probability. These findings motivate for improving the production schedule, the system design, and the operational strategies.
    Keywords: ARIMA models, Copula function, Conditional probability, District heating system, Outdoor temperature, Peak heat demand
    JEL: C10 C32 P28
    Date: 2018–07

This nep-ets issue is ©2018 by Jaqueson K. Galimberti. It is provided as is without any express or implied warranty. It may be freely redistributed in whole or in part for any purpose. If distributed in part, please include this notice.
General information on the NEP project can be found at For comments please write to the director of NEP, Marco Novarese at <>. Put “NEP” in the subject, otherwise your mail may be rejected.
NEP’s infrastructure is sponsored by the School of Economics and Finance of Massey University in New Zealand.