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Chang Sik Kim

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. Yoosoon Chang & Yongok Choi & Chang Sik Kim & J. Isaac Miller & Joon Y. Park, 2019. "Forecasting Regional Long-Run Energy Demand: A Functional Coefficient Panel Approach," Working Papers 1915, Department of Economics, University of Missouri.

    Cited by:

    1. Grzegorz Ślusarz & Dariusz Twaróg & Barbara Gołębiewska & Marek Cierpiał-Wolan & Jarosław Gołębiewski & Philipp Plutecki, 2023. "The Role of Biogas Potential in Building the Energy Independence of the Three Seas Initiative Countries," Energies, MDPI, vol. 16(3), pages 1-23, January.
    2. Rao, Congjun & Zhang, Yue & Wen, Jianghui & Xiao, Xinping & Goh, Mark, 2023. "Energy demand forecasting in China: A support vector regression-compositional data second exponential smoothing model," Energy, Elsevier, vol. 263(PC).
    3. Hilde C. Bjornland & Malin C. Jensen & Leif Anders Thorsrud, 2024. "Business Cycle and Health Dynamics during the COVID-19 Pandemic: A Scandinavian Perspective," CAMA Working Papers 2024-19, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    4. Yoosoon Chang & Yongok Choi & Chang Sik Kim & J. Isaac Miller & Joon Y. Park, 2024. "Common Trends and Country Specific Heterogeneities in Long-Run World Energy Consumption," CAMA Working Papers 2024-04, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    5. Brantley Liddle, 2022. "What Is the Temporal Path of the GDP Elasticity of Energy Consumption in OECD Countries? An Assessment of Previous Findings and New Evidence," Energies, MDPI, vol. 15(10), pages 1-12, May.
    6. Cao, Xin & Zhang, Zechen & Qian, Yuan & Wen, Zongguo, 2024. "The spatial pattern, driving factors and evolutionary trend of energy cooperation and consumption in the “Belt and Road Initiative” countries," Energy, Elsevier, vol. 306(C).
    7. Xin Ma & Yubin Cai & Hong Yuan & Yanqiao Deng, 2023. "Partially Linear Component Support Vector Machine for Primary Energy Consumption Forecasting of the Electric Power Sector in the United States," Sustainability, MDPI, vol. 15(9), pages 1-26, April.
    8. Wang, You & Gong, Xu, 2022. "Analyzing the difference evolution of provincial energy consumption in China using the functional data analysis method," Energy Economics, Elsevier, vol. 105(C).
    9. J. Isaac Miller & Kyungsik Nam, 2021. "Modeling Peak Electricity Demand: A Semiparametric Approach Using Weather-Driven Cross Temperature Response Functions," Working Papers 2112, Department of Economics, University of Missouri.
    10. Zhao, Jing & Miller, J. Isaac & Binfield, Julian & Thompson, Wyatt, 2022. "Modeling and Forecasting Agricultural Commodity Support in the Developing Countries," Commissioned Papers 321785, International Agricultural Trade Research Consortium.
    11. Bennedsen, Mikkel & Hillebrand, Eric & Jensen, Sebastian, 2023. "A neural network approach to the environmental Kuznets curve," Energy Economics, Elsevier, vol. 126(C).
    12. Liddle, Brantley, 2023. "Is timing everything? Assessing the evidence on whether energy/electricity demand elasticities are time-varying," Energy Economics, Elsevier, vol. 124(C).

  2. Yoosoon Chang & Robert K. Kaufmann & Chang Sik Kim & J. Isaac Miller & Joon Y. Park & Sungkeun Park, 2016. "Evaluating trends in time series of distributions: A spatial fingerprint of human effects on climate," Working Papers 1622, Department of Economics, University of Missouri, revised 17 Sep 2018.

    Cited by:

    1. C. Vladimir Rodr'iguez-Caballero & Esther Ruiz, 2024. "Temperature in the Iberian Peninsula: Trend, seasonality, and heterogeneity," Papers 2406.14145, arXiv.org.
    2. Won-Ki Seo, 2020. "Functional Principal Component Analysis for Cointegrated Functional Time Series," Papers 2011.12781, arXiv.org, revised Apr 2023.
    3. Chen, Liang & Ramos Ramirez, Andrey David, 2023. "Heterogeneous Predictive Association of CO2 with Global Warming," UC3M Working papers. Economics 36451, Universidad Carlos III de Madrid. Departamento de Economía.
    4. Phella, Anthoulla & Gabriel, Vasco J. & Martins, Luis F., 2024. "Predicting tail risks and the evolution of temperatures," Energy Economics, Elsevier, vol. 131(C).
    5. Hilde C. Bjornland & Malin C. Jensen & Leif Anders Thorsrud, 2024. "Business Cycle and Health Dynamics during the COVID-19 Pandemic: A Scandinavian Perspective," CAMA Working Papers 2024-19, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    6. Morana, Claudio & Sbrana, Giacomo, 2019. "Climate change implications for the catastrophe bonds market: An empirical analysis," Economic Modelling, Elsevier, vol. 81(C), pages 274-294.
    7. Marc Gronwald, 2023. "Explosive Temperatures," CESifo Working Paper Series 10680, CESifo.
    8. Won‐Ki Seo, 2024. "Functional principal component analysis for cointegrated functional time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 45(2), pages 320-330, March.
    9. Mohitosh Kejriwal & Xuewen Yu & Pierre Perron, 2020. "Bootstrap Procedures for Detecting Multiple Persistence Shifts in Heteroskedastic Time Series," Boston University - Department of Economics - Working Papers Series WP2020-009, Boston University - Department of Economics.
    10. Kyungsik Nam, 2021. "Nonlinear Cointegrating Regression of the Earth’s Surface Mean Temperature Anomalies on Total Radiative Forcing," Econometrics, MDPI, vol. 9(1), pages 1-25, February.
    11. Yoonseok Lee & Donggyu Sul, 2023. "Depth-weighted Forecast Combination: Application to COVID-19 Cases," Advances in Econometrics, in: Essays in Honor of Joon Y. Park: Econometric Methodology in Empirical Applications, volume 45, pages 235-260, Emerald Group Publishing Limited.
    12. Li Chen & Jiti Gao & Farshid Vahid, 2019. "Global temperatures and greenhouse gases - a common features approach," Working Papers 2019-07-15, Wang Yanan Institute for Studies in Economics (WISE), Xiamen University.
    13. Yoosoon Chang & Yongok Choi & Chang Sik Kim & J. Isaac Miller & Joon Y. Park, 2024. "Common Trends and Country Specific Heterogeneities in Long-Run World Energy Consumption," CAMA Working Papers 2024-04, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    14. Yoosoon Chang & Yongok Choi & Chang Sik Kim & J. Isaac Miller & Joon Y. Park, 2019. "Forecasting Regional Long-Run Energy Demand: A Functional Coefficient Panel Approach," Working Papers 1915, Department of Economics, University of Missouri.
    15. González-Rivera, Gloria & Rodríguez Caballero, Carlos Vladimir, 2023. "Modelling intervals of minimum/maximum temperatures in the Iberian Peninsula," DES - Working Papers. Statistics and Econometrics. WS 37968, Universidad Carlos III de Madrid. Departamento de Estadística.
    16. Manveer Kaur Mangat & Erhard Reschenhofer, 2020. "Frequency-Domain Evidence for Climate Change," Econometrics, MDPI, vol. 8(3), pages 1-15, July.
    17. Pretis, Felix, 2021. "Exogeneity in climate econometrics," Energy Economics, Elsevier, vol. 96(C).
    18. Ar'anzazu de Juan & Pilar Poncela & Vladimir Rodr'iguez-Caballero & Esther Ruiz, 2022. "Economic activity and climate change," Papers 2206.03187, arXiv.org, revised Jun 2022.
    19. Hee Soo (test record) Kim & Christian Matthes & Toan Phan, 2011. "Extreme Weather and the Macroeconomy," Working Paper 21-14, Federal Reserve Bank of Richmond.
    20. In Choi, 2023. "Does climate change affect economic data?," Empirical Economics, Springer, vol. 64(6), pages 2939-2956, June.
    21. Yoosoon Chang & J. Isaac Miller & Joon K. Park, 2024. "Shocking Climate: Identifying Economic Damages from Anthropogenic and Natural Climate Change," CAEPR Working Papers 2024-007 Classification-E, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.

  3. Yoosoon Chang & Chang Sik Kim & J. Isaac Miller & Joon Y. Park & Sungkeun Park, 2015. "A New Approach to Modeling the Effects of Temperature Fluctuations on Monthly Electricity Demand," Working Papers 1512, Department of Economics, University of Missouri.

    Cited by:

    1. Hocheol Jeon, 2019. "The Impact of Climate Change on Passenger Vehicle Fuel Consumption: Evidence from U.S. Panel Data," Energies, MDPI, vol. 12(23), pages 1-15, November.
    2. Harish, Santosh & Singh, Nishmeet & Tongia, Rahul, 2020. "Impact of temperature on electricity demand: Evidence from Delhi and Indian states," Energy Policy, Elsevier, vol. 140(C).
    3. Alimohammadisagvand, Behrang & Jokisalo, Juha & Sirén, Kai, 2018. "Comparison of four rule-based demand response control algorithms in an electrically and heat pump-heated residential building," Applied Energy, Elsevier, vol. 209(C), pages 167-179.
    4. Hu, Wenxuan & Scholz, Yvonne & Yeligeti, Madhura & Deng, Ying & Jochem, Patrick, 2024. "Future electricity demand for Europe: Unraveling the dynamics of the Temperature Response Function," Applied Energy, Elsevier, vol. 368(C).
    5. Mosquera-López, Stephanía & Uribe, Jorge M. & Manotas-Duque, Diego F., 2018. "Effect of stopping hydroelectric power generation on the dynamics of electricity prices: An event study approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 456-467.
    6. Xu, Chang & Katchova, Ani L., 2019. "Predicting Soybean Yield with NDVI Using a Flexible Fourier Transform Model," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 51(3), pages 402-416, August.
    7. Stéphane AURAY & Vincent CAPONI, 2020. "A Vector Autoregressive Model of Forecast Electricity Consumption in France," Working Papers 2020-06, Center for Research in Economics and Statistics.
    8. Kamal Chapagain & Somsak Kittipiyakul & Pisut Kulthanavit, 2020. "Short-Term Electricity Demand Forecasting: Impact Analysis of Temperature for Thailand," Energies, MDPI, vol. 13(10), pages 1-29, May.
    9. J. Isaac Miller & Kyungsik Nam, 2021. "Modeling Peak Electricity Demand: A Semiparametric Approach Using Weather-Driven Cross Temperature Response Functions," Working Papers 2112, Department of Economics, University of Missouri.
    10. Bigerna, Simona, 2018. "Estimating temperature effects on the Italian electricity market," Energy Policy, Elsevier, vol. 118(C), pages 257-269.
    11. Tian, Chuyin & Huang, Guohe & Piwowar, Joseph M. & Yeh, Shin-Cheng & Lu, Chen & Duan, Ruixin & Ren, Jiayan, 2022. "Stochastic RCM-driven cooling and heating energy demand analysis for residential building," Renewable and Sustainable Energy Reviews, Elsevier, vol. 153(C).
    12. Ha-Hyun Jo & Minwoo Jang & Jaehyeok Kim, 2020. "How Population Age Distribution Affects Future Electricity Demand in Korea: Applying Population Polynomial Function," Energies, MDPI, vol. 13(20), pages 1-17, October.
    13. Gautam, Tej K. & Paudel, Krishna P., 2018. "Estimating sectoral demands for electricity using the pooled mean group method," Applied Energy, Elsevier, vol. 231(C), pages 54-67.
    14. Manner, Hans & Alavi Fard, Farzad & Pourkhanali, Armin & Tafakori, Laleh, 2019. "Forecasting the joint distribution of Australian electricity prices using dynamic vine copulae," Energy Economics, Elsevier, vol. 78(C), pages 143-164.
    15. Ang, B.W. & Wang, H. & Ma, Xiaojing, 2017. "Climatic influence on electricity consumption: The case of Singapore and Hong Kong," Energy, Elsevier, vol. 127(C), pages 534-543.
    16. Leonardo Bortolan & Atreya Dey & Luca Taschini, 2024. "Volatile Temperatures and Their Effects on Equity Returns and Firm Performance," CESifo Working Paper Series 11438, CESifo.
    17. Wang, Chong & Ju, Ping & Wu, Feng & Pan, Xueping & Wang, Zhaoyu, 2022. "A systematic review on power system resilience from the perspective of generation, network, and load," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).

  4. Yoosoon Chang & Robert K. Kaufmann & Chang Sik Kim & J. Isaac Miller & Joon Y. Park & Sungkeun Park, 2015. "Time Series Analysis of Global Temperature Distributions: Identifying and Estimating Persistent Features in Temperature Anomalies," Working Papers 1513, Department of Economics, University of Missouri, revised 25 Jul 2016.

    Cited by:

    1. J. Isaac Miller, 2017. "Local Climate Sensitivity: A Statistical Approach for a Spatially Heterogeneous Planet," Working Papers 1702, Department of Economics, University of Missouri.
    2. Claudio Morana & Giacomo Sbrana, 2018. "Some Financial Implications of Global Warming: an Empirical Assessment," Working Papers 2018.01, Fondazione Eni Enrico Mattei.
    3. Morana, Claudio & Sbrana, Giacomo, 2017. "Temperature Anomalies, Radiative Forcing and ENSO," MITP: Mitigation, Innovation and Transformation Pathways 253732, Fondazione Eni Enrico Mattei (FEEM).
    4. Gadea Rivas, María Dolores & Gonzalo, Jesús, 2020. "Trends in distributional characteristics: Existence of global warming," Journal of Econometrics, Elsevier, vol. 214(1), pages 153-174.

  5. Yoosoon Chang & Chang Sik Kim & J. Isaac Miller & Joon Y. Park & Sungkeun Park, 2014. "Time-varying Long-run Income and Output Elasticities of Electricity Demand," Working Papers 1409, Department of Economics, University of Missouri.

    Cited by:

    1. Yuo-Hsien Shiau & Su-Fen Yang & Rishan Adha & Syamsiyatul Muzayyanah, 2022. "Modeling Industrial Energy Demand in Relation to Subsector Manufacturing Output and Climate Change: Artificial Neural Network Insights," Sustainability, MDPI, vol. 14(5), pages 1-18, March.
    2. Hocheol Jeon, 2019. "The Impact of Climate Change on Passenger Vehicle Fuel Consumption: Evidence from U.S. Panel Data," Energies, MDPI, vol. 12(23), pages 1-15, November.
    3. Julián Pérez-García & Julián Moral-Carcedo, 2017. "Why Electricity Demand Is Highly Income-Elastic in Spain: A Cross-Country Comparison Based on an Index-Decomposition Analysis," Energies, MDPI, vol. 10(3), pages 1-20, March.
    4. Hyo-Jin Kim & Gyeong-Sam Kim & Seung-Hoon Yoo, 2019. "Demand Function for Industrial Electricity: Evidence from South Korean Manufacturing Sector," Sustainability, MDPI, vol. 11(18), pages 1-11, September.
    5. Kyungsik Nam, 2021. "Nonlinear Cointegrating Regression of the Earth’s Surface Mean Temperature Anomalies on Total Radiative Forcing," Econometrics, MDPI, vol. 9(1), pages 1-25, February.
    6. Daniel de Abreu Pereira Uhr & Júlia Gallego Ziero Uhr, André Luis Squarize Chagas, 2017. "Estimation of price and income elasticities for the Brazilian household electricity demand," Working Papers, Department of Economics 2017_12, University of São Paulo (FEA-USP).
    7. Kyungsik Nam & Sungro Lee & Hocheol Jeon, 2020. "Nonlinearity between CO 2 Emission and Economic Development: Evidence from a Functional Coefficient Panel Approach," Sustainability, MDPI, vol. 12(24), pages 1-10, December.
    8. Pereira Uhr, Daniel de Abreu & Squarize Chagas, André Luis & Ziero Uhr, Júlia Gallego, 2019. "Estimation of elasticities for electricity demand in Brazilian households and policy implications," Energy Policy, Elsevier, vol. 129(C), pages 69-79.
    9. Pérez-García, Julián & Moral-Carcedo, Julián, 2016. "Analysis and long term forecasting of electricity demand trough a decomposition model: A case study for Spain," Energy, Elsevier, vol. 97(C), pages 127-143.
    10. Yasunobu Wakashiro, 2019. "Estimating price elasticity of demand for electricity: the case of Japanese manufacturing industry," International Journal of Economic Policy Studies, Springer, vol. 13(1), pages 173-191, January.
    11. Polbin, Andrey & Skrobotov, Anton, 2022. "On decrease in oil price elasticity of GDP and investment in Russia," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 66, pages 5-24.
    12. Hyo-Jin Kim & Jae-Sung Paek & Seung-Hoon Yoo, 2019. "Price Elasticity of Heat Demand in South Korean Manufacturing Sector: An Empirical Investigation," Sustainability, MDPI, vol. 11(21), pages 1-10, November.
    13. Ribó-Pérez, David & Van der Weijde, Adriaan H. & Álvarez-Bel, Carlos, 2019. "Effects of self-generation in imperfectly competitive electricity markets: The case of Spain," Energy Policy, Elsevier, vol. 133(C).
    14. Salisu, Afees A. & Ayinde, Taofeek O., 2016. "Modeling energy demand: Some emerging issues," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1470-1480.
    15. Soon, Byung Min & Thompson, Wyatt, 2017. "Testing for Persistent Japanese Beef Trade Impacts from BSE Using a Time-Varying Armington Model," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 259150, Agricultural and Applied Economics Association.
    16. Yoosoon Chang & Chang Sik Kim & J. Isaac Miller & Joon Y. Park & Sungkeun Park, 2015. "A New Approach to Modeling the Effects of Temperature Fluctuations on Monthly Electricity Demand," Working Papers 1512, Department of Economics, University of Missouri.
    17. Jeyhun I. Mikayilov & Fakhri J. Hasanov & Carlo A. Bollino & Ceyhun Mahmudlu, 2017. "Modeling of Electricity Demand for Azerbaijan: Time-Varying Coefficient Cointegration Approach," Energies, MDPI, vol. 10(11), pages 1-12, November.
    18. Ozturk, Ilhan & Arisoy, Ibrahim, 2016. "An estimation of crude oil import demand in Turkey: Evidence from time-varying parameters approach," Energy Policy, Elsevier, vol. 99(C), pages 174-179.
    19. Jeyhun I. Mikayilov & Fakhri J. Hasanov & Marzio Galeotti, 2018. "Decoupling of C02 Emissions and GDP: A Time-Varying Cointegration Approach," IEFE Working Papers 101, IEFE, Center for Research on Energy and Environmental Economics and Policy, Universita' Bocconi, Milano, Italy.
    20. Nikos Sakkas & Sofia Yfanti & Costas Daskalakis & Eduard Barbu & Marharyta Domnich, 2021. "Interpretable Forecasting of Energy Demand in the Residential Sector," Energies, MDPI, vol. 14(20), pages 1-17, October.
    21. Hasanov, Fakhri J. & Aliyev, Ruslan & Taskin, Dilvin & Suleymanov, Elchin, 2023. "Oil rents and non-oil economic growth in CIS oil exporters. The role of financial development," Resources Policy, Elsevier, vol. 82(C).
    22. Kaneko, Nanae & Fujimoto, Yu & Kabe, Satoshi & Hayashida, Motonari & Hayashi, Yasuhiro, 2020. "Sparse modeling approach for identifying the dominant factors affecting situation-dependent hourly electricity demand," Applied Energy, Elsevier, vol. 265(C).
    23. Hortay, Olivér & Szőke, Tamás, 2019. "Keresleti árrugalmasság becslése a magyar villamosenergia-piacon [Estimating demand-price elasticity on the Hungarian electric energy market]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(7), pages 788-804.
    24. Wang, Banban & Wei, Jie & Tan, Xiujie & Su, Bin, 2021. "The sectorally heterogeneous and time-varying price elasticities of energy demand in China," Energy Economics, Elsevier, vol. 102(C).
    25. J. Isaac Miller & Kyungsik Nam, 2021. "Modeling Peak Electricity Demand: A Semiparametric Approach Using Weather-Driven Cross Temperature Response Functions," Working Papers 2112, Department of Economics, University of Missouri.
    26. Jeyhun I. Mikayilov & Shahriyar Mukhtarov & Jeyhun Mammadov, 2020. "Gasoline Demand Elasticities at the Backdrop of Lower Oil Prices: Fuel-Subsidizing Country Case," Energies, MDPI, vol. 13(24), pages 1-18, December.
    27. Asuamah Yeboah, Samuel, 2018. "Do government activities determine electricity consumption in Ghana? An empirical investigation," MPRA Paper 89408, University Library of Munich, Germany.
    28. Yoosoon Chang & Yongok Choi & Chang Sik Kim & Joon Y. Park & J. Isaac Miller, 2013. "Disentangling Temporal Patterns in Elasticities: A Functional Coefficient Panel Analysis of Electricity Demand," Working Papers 1320, Department of Economics, University of Missouri.
    29. Ha-Hyun Jo & Minwoo Jang & Jaehyeok Kim, 2020. "How Population Age Distribution Affects Future Electricity Demand in Korea: Applying Population Polynomial Function," Energies, MDPI, vol. 13(20), pages 1-17, October.
    30. Sharimakin, Akinsehinwa, 2021. "Modelling asymmetric price responses of industrial energy demand with a dynamic hierarchical model," Energy Economics, Elsevier, vol. 98(C).
    31. Fukushige, Mototsugu & Yamawaki, Hiroshige, 2015. "The relationship between an electricity supply ceiling and economic growth: An application of disequilibrium modeling to Taiwan," Journal of Asian Economics, Elsevier, vol. 36(C), pages 14-23.
    32. Liddle, Brantley & Smyth, Russell & Zhang, Xibin, 2020. "Time-varying income and price elasticities for energy demand: Evidence from a middle-income panel," Energy Economics, Elsevier, vol. 86(C).
    33. Martin Falk & Xiang Lin, 2018. "Income elasticity of overnight stays over seven decades," Tourism Economics, , vol. 24(8), pages 1015-1028, December.
    34. Agnolucci, Paolo & De Lipsis, Vincenzo & Arvanitopoulos, Theodoros, 2017. "Modelling UK sub-sector industrial energy demand," Energy Economics, Elsevier, vol. 67(C), pages 366-374.
    35. Keita Honjo & Hiroto Shiraki & Shuichi Ashina, 2018. "Dynamic linear modeling of monthly electricity demand in Japan: Time variation of electricity conservation effect," PLOS ONE, Public Library of Science, vol. 13(4), pages 1-23, April.
    36. Wang, Nan & Mogi, Gento, 2017. "Industrial and residential electricity demand dynamics in Japan: How did price and income elasticities evolve from 1989 to 2014?," Energy Policy, Elsevier, vol. 106(C), pages 233-243.
    37. Daniel Morais de Souza & Rogerio Silva de Mattos & Alexandre Zanini, 2022. "Estimating Elasticities for the Residential Demand of Electricity in Brazil Using Cointegration Models," International Journal of Energy Economics and Policy, Econjournals, vol. 12(2), pages 315-324, March.
    38. Joo, Young C. & Park, Sung Y., 2017. "Oil prices and stock markets: Does the effect of uncertainty change over time?," Energy Economics, Elsevier, vol. 61(C), pages 42-51.
    39. Chang Sik Kim & Sunghyun Kim & Yunjong Wang, 2018. "RMB Bloc in East Asia: Too Early to Talk About It?," Asian Economic Papers, MIT Press, vol. 17(3), pages 31-48, Fall.

  6. Yoosoon Chang & Yongok Choi & Chang Sik Kim & Joon Y. Park & J. Isaac Miller, 2013. "Disentangling Temporal Patterns in Elasticities: A Functional Coefficient Panel Analysis of Electricity Demand," Working Papers 1320, Department of Economics, University of Missouri.

    Cited by:

    1. Julián Pérez-García & Julián Moral-Carcedo, 2017. "Why Electricity Demand Is Highly Income-Elastic in Spain: A Cross-Country Comparison Based on an Index-Decomposition Analysis," Energies, MDPI, vol. 10(3), pages 1-20, March.
    2. Brantley Liddle, 2022. "What Is the Temporal Path of the GDP Elasticity of Energy Consumption in OECD Countries? An Assessment of Previous Findings and New Evidence," Energies, MDPI, vol. 15(10), pages 1-12, May.
    3. Kyungsik Nam & Sungro Lee & Hocheol Jeon, 2020. "Nonlinearity between CO 2 Emission and Economic Development: Evidence from a Functional Coefficient Panel Approach," Sustainability, MDPI, vol. 12(24), pages 1-10, December.
    4. Chang, Yoosoon & Kim, Chang Sik & Miller, J. Isaac & Park, Joon Y. & Park, Sungkeun, 2014. "Time-varying Long-run Income and Output Elasticities of Electricity Demand with an Application to Korea," Energy Economics, Elsevier, vol. 46(C), pages 334-347.
    5. Salisu, Afees A. & Ayinde, Taofeek O., 2016. "Modeling energy demand: Some emerging issues," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1470-1480.
    6. Fakhri J. Hasanov & Lester C. Hunt & Ceyhun I. Mikayilov, 2016. "Modeling and Forecasting Electricity Demand in Azerbaijan Using Cointegration Techniques," Energies, MDPI, vol. 9(12), pages 1-31, December.
    7. Jeyhun I. Mikayilov & Fakhri J. Hasanov & Carlo A. Bollino & Ceyhun Mahmudlu, 2017. "Modeling of Electricity Demand for Azerbaijan: Time-Varying Coefficient Cointegration Approach," Energies, MDPI, vol. 10(11), pages 1-12, November.
    8. Yoosoon Chang & Yongok Choi & Chang Sik Kim & J. Isaac Miller & Joon Y. Park, 2019. "Forecasting Regional Long-Run Energy Demand: A Functional Coefficient Panel Approach," Working Papers 1915, Department of Economics, University of Missouri.
    9. J. Isaac Miller & Kyungsik Nam, 2021. "Modeling Peak Electricity Demand: A Semiparametric Approach Using Weather-Driven Cross Temperature Response Functions," Working Papers 2112, Department of Economics, University of Missouri.
    10. Bennedsen, Mikkel & Hillebrand, Eric & Jensen, Sebastian, 2023. "A neural network approach to the environmental Kuznets curve," Energy Economics, Elsevier, vol. 126(C).
    11. Yicong Lin & Mingxuan Song, 2023. "Robust bootstrap inference for linear time-varying coefficient models: Some Monte Carlo evidence," Tinbergen Institute Discussion Papers 23-049/III, Tinbergen Institute.
    12. Mohammad Nure Alam, 2021. "Accessing the Effect of Renewables on the Wholesale Power Market," International Journal of Energy Economics and Policy, Econjournals, vol. 11(2), pages 341-360.
    13. Jeyhun Mikayilov & Fred Joutz & Fakhri Hasanov, 2019. "Gasoline Demand in Saudi Arabia: Are the Price and Income Elasticities Constant?," Discussion Papers ks--2019-dp81, King Abdullah Petroleum Studies and Research Center.
    14. Jeyhun I. Mikayilov & Shahriyar Mukhtarov & Jeyhun Mammadov, 2020. "Gasoline Demand Elasticities at the Backdrop of Lower Oil Prices: Fuel-Subsidizing Country Case," Energies, MDPI, vol. 13(24), pages 1-18, December.
    15. Liddle, Brantley & Parker, Steven & Hasanov, Fakhri, 2023. "Why has the OECD long-run GDP elasticity of economy-wide electricity demand declined? Because the electrification of energy services has saturated," Energy Economics, Elsevier, vol. 125(C).
    16. Liddle, Brantley, 2023. "Is timing everything? Assessing the evidence on whether energy/electricity demand elasticities are time-varying," Energy Economics, Elsevier, vol. 124(C).
    17. Meangbua, Onicha & Dhakal, Shobhakar & Kuwornu, John K.M., 2019. "Factors influencing energy requirements and CO2 emissions of households in Thailand: A panel data analysis," Energy Policy, Elsevier, vol. 129(C), pages 521-531.
    18. Gao, Jiti & Peng, Bin & Smyth, Russell, 2021. "On income and price elasticities for energy demand: A panel data study," Energy Economics, Elsevier, vol. 96(C).
    19. Ha-Hyun Jo & Minwoo Jang & Jaehyeok Kim, 2020. "How Population Age Distribution Affects Future Electricity Demand in Korea: Applying Population Polynomial Function," Energies, MDPI, vol. 13(20), pages 1-17, October.
    20. Friedrich, Marina & Lin, Yicong, 2024. "Sieve bootstrap inference for linear time-varying coefficient models," Journal of Econometrics, Elsevier, vol. 239(1).
    21. Yoosoon Chang & Chang Sik Kim & J. Isaac Miller & Joon Y. Park & Sungkeun Park, 2014. "Time-varying Long-run Income and Output Elasticities of Electricity Demand," Working Papers 1409, Department of Economics, University of Missouri.
    22. Liddle, Brantley & Smyth, Russell & Zhang, Xibin, 2020. "Time-varying income and price elasticities for energy demand: Evidence from a middle-income panel," Energy Economics, Elsevier, vol. 86(C).
    23. Yongok Choi, 2020. "Impact of Longevity Risks on the Korean Government: Proposing a New Mortality Forecasting Model," Korean Economic Review, Korean Economic Association, vol. 36, pages 201-225.

  7. Peter C.B. Phillips & Chang Sik Kim, 2007. "Long Run Covariance Matrices for Fractionally Integrated Processes," Cowles Foundation Discussion Papers 1611, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Robinson Kruse & Christian Leschinski & Michael Will, 2016. "Comparing Predictive Accuracy under Long Memory - With an Application to Volatility Forecasting," CREATES Research Papers 2016-17, Department of Economics and Business Economics, Aarhus University.
    2. Leschinski, Christian, 2017. "On the memory of products of long range dependent time series," Economics Letters, Elsevier, vol. 153(C), pages 72-76.
    3. McAdam, Peter & Christopoulos, Dimitris, 2015. "Do financial reforms help stabilize inequality?," Working Paper Series 1780, European Central Bank.
    4. Farzad Sabzikar & Qiying Wang & Peter C.B. Phillips, 2018. "Asymptotic Theory for Near Integrated Process Driven by Tempered Linear Process," Cowles Foundation Discussion Papers 2131, Cowles Foundation for Research in Economics, Yale University.
    5. Peter C.B. Phillips, 2008. "Long Memory and Long Run Variation," Cowles Foundation Discussion Papers 1656, Cowles Foundation for Research in Economics, Yale University.
    6. Qunyong Wang & Na Wu, 2012. "Long-run covariance and its applications in cointegration regression," Stata Journal, StataCorp LP, vol. 12(3), pages 525-542, September.

  8. Chang Sik Kim & Peter C.B. Phillips, 2006. "Log Periodogram Regression: The Nonstationary Case," Cowles Foundation Discussion Papers 1587, Cowles Foundation for Research in Economics, Yale University.

    Cited by:

    1. Guglielmo Maria Caporale & Luis Alberiko Gil-Alana & Pedro José Piqueras Martínez, 2024. "Dynamic Factor Models and Fractional Integration – With an Application to US Real Economic Activity," CESifo Working Paper Series 11486, CESifo.
    2. Hector Carcel & Luis A. Gil-Alana, 2018. "Inflation analysis in the Central American Monetary Council," Empirical Economics, Springer, vol. 54(2), pages 547-565, March.
    3. Tan, Zhengxun & Liu, Juan & Chen, Juanjuan, 2021. "Detecting stock market turning points using wavelet leaders method," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 565(C).
    4. Marcel Aloy & Gilles de Truchis, 2015. "Optimal Estimation Strategies for Bivariate Fractional Cointegration Systems and the Co-persistence Analysis of Stock Market Realized Volatilities," Post-Print hal-01410660, HAL.
    5. Davidson James & Rambaccussing Dooruj, 2015. "A Test of the Long Memory Hypothesis Based on Self-Similarity," Journal of Time Series Econometrics, De Gruyter, vol. 7(2), pages 115-141, July.
    6. Giorgio Canarella & Stephen M Miller, 2017. "Inflation Persistence Before and After Inflation Targeting: A Fractional Integration Approach," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 43(1), pages 78-103, January.
    7. Arteche, Josu & Orbe, Jesus, 2009. "Using the bootstrap for finite sample confidence intervals of the log periodogram regression," Computational Statistics & Data Analysis, Elsevier, vol. 53(6), pages 1940-1953, April.
    8. Peter C.B. Phillips, 1999. "Unit Root Log Periodogram Regression," Cowles Foundation Discussion Papers 1244, Cowles Foundation for Research in Economics, Yale University.
    9. Kühl, Michael, 2008. "Strong comovements of exchange rates: Theoretical and empirical cases when currencies become the same asset," University of Göttingen Working Papers in Economics 76, University of Goettingen, Department of Economics.
    10. Frank S. Nielsen, 2011. "Local Whittle estimation of multi‐variate fractionally integrated processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 32(3), pages 317-335, May.
    11. Lenin Arango-Castillo & Francisco J. Martínez-Ramírez & María José Orraca, 2024. "Univariate Measures of Persistence: A Comparative Analysis," Working Papers 2024-11, Banco de México.
    12. Katsumi Shimotsu & Peter C.B. Phillips, 2000. "Local Whittle Estimation in Nonstationary and Unit Root Cases," Cowles Foundation Discussion Papers 1266, Cowles Foundation for Research in Economics, Yale University, revised Sep 2003.
    13. Rangan Gupta & Christophe André & Luis Gil-Alana, 2015. "Comovement in Euro area housing prices: A fractional cointegration approach," Urban Studies, Urban Studies Journal Limited, vol. 52(16), pages 3123-3143, December.
    14. Gilles Dufrénot & Valérie Mignon & Théo Naccache, 2012. "The slow convergence of per capita income between the developing countries: ‘growth resistance’ and sometimes ‘growth tragedy’," Post-Print hal-01385800, HAL.
    15. Chaker Aloui & Hela BEN HAMIDA, 2015. "Estimation and Performance Assessment of Value-at-Risk and Expected Shortfall Based on Long-Memory GARCH-Class Models," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 65(1), pages 30-54, January.
    16. Basma Bekdache & Christopher F. Baum, 1999. "A re-evaluation of empirical tests of the Fisher hypothesis," Computing in Economics and Finance 1999 944, Society for Computational Economics, revised 18 Sep 2000.
    17. Per Frederiksen & Frank S. Nielsen, 2008. "Estimation of Dynamic Models with Nonparametric Simulated Maximum Likelihood," CREATES Research Papers 2008-59, Department of Economics and Business Economics, Aarhus University.
    18. Rustam Ibragimov & Jihyun Kim & Anton Skrobotov, 2020. "New robust inference for predictive regressions," Papers 2006.01191, arXiv.org, revised Mar 2023.
    19. Härdle, Wolfgang Karl & Mungo, Julius, 2008. "Value-at-risk and expected shortfall when there is long range dependence," SFB 649 Discussion Papers 2008-006, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    20. Frank S. Nielsen, 2009. "Local Whittle estimation of multivariate fractionally integrated processes," CREATES Research Papers 2009-38, Department of Economics and Business Economics, Aarhus University.
    21. Giorgio Canarella & Stephen M. Miller, 2016. "Inflation Persistence and Structural Breaks: The Experience of Inflation Targeting Countries and the US," Working papers 2016-11, University of Connecticut, Department of Economics.
    22. Ling Hu & Peter C.B. Phillips, 2002. "Dynamics of the Federal Funds Target Rate: A Nonstationary Discrete Choice Approach," Cowles Foundation Discussion Papers 1365, Cowles Foundation for Research in Economics, Yale University.
    23. Marcel Aloy & Gilles de Truchis, 2013. "Optimal Estimation Strategies for Bivariate Fractional Cointegration Systems," AMSE Working Papers 1353, Aix-Marseille School of Economics, France, revised 29 Oct 2013.
    24. Frank S. Nielsen, 2008. "Local polynomial Whittle estimation covering non-stationary fractional processes," CREATES Research Papers 2008-28, Department of Economics and Business Economics, Aarhus University.
    25. Katsumi Shimotsu, 2006. "Exact Local Whittle Estimation of Fractional Integration with Unknown Mean and Time Trend," Working Paper 1061, Economics Department, Queen's University.
    26. Kufenko, Vadim, 2016. "Spurious periodicities in cliometric series: Simultaneous testing," Violette Reihe: Schriftenreihe des Promotionsschwerpunkts "Globalisierung und Beschäftigung" 48/2016, University of Hohenheim, Carl von Ossietzky University Oldenburg, Evangelisches Studienwerk.
    27. Gil-Alana, Luis A. & Yaya, OlaOluwa S. & Awe, Olushina O., 2017. "Time series analysis of co-movements in the prices of gold and oil: Fractional cointegration approach," Resources Policy, Elsevier, vol. 53(C), pages 117-124.
    28. Arteche, Josu, 2024. "Bootstrapping long memory time series: Application in low frequency estimators," Econometrics and Statistics, Elsevier, vol. 29(C), pages 1-15.
    29. Gündüz, Yalin & Kaya, Orcun, 2013. "Sovereign default swap market efficiency and country risk in the eurozone," Discussion Papers 08/2013, Deutsche Bundesbank.

Articles

  1. Minsoo Jeong & Chang Sik Kim & Haeseong Park, 2022. "Re-examining The Time-varying Relationship Between Health and Income Distributions," International Economic Journal, Taylor & Francis Journals, vol. 36(2), pages 158-170, April.

    Cited by:

    1. Byaro, Mwoya & Mafwolo, Gemma & Ngereza, Caroline, 2023. "Does unemployment in sub-Saharan Africa have asymmetric effects on health? A panel quantile approach," The Journal of Economic Asymmetries, Elsevier, vol. 28(C).

  2. Chang, Yoosoon & Choi, Yongok & Kim, Chang Sik & Miller, J. Isaac & Park, Joon Y., 2021. "Forecasting regional long-run energy demand: A functional coefficient panel approach," Energy Economics, Elsevier, vol. 96(C).
    See citations under working paper version above.
  3. Soondong Hong & Heejoon Han & Chang Sik Kim, 2020. "World distribution of income for 1970–2010: dramatic reduction in world income inequality during the 2000s," Empirical Economics, Springer, vol. 59(2), pages 765-798, August.

    Cited by:

    1. Jarle Aarstad & Olav A. Kvitastein, 2021. "Do Operating Profits Induce a Wage Premium Equally Shared among Employees Earning High or Low Incomes?," Economies, MDPI, vol. 9(2), pages 1-7, May.

  4. Chang, Yoosoon & Kaufmann, Robert K. & Kim, Chang Sik & Miller, J. Isaac & Park, Joon Y. & Park, Sungkeun, 2020. "Evaluating trends in time series of distributions: A spatial fingerprint of human effects on climate," Journal of Econometrics, Elsevier, vol. 214(1), pages 274-294.
    See citations under working paper version above.
  5. Chang Sik Kim & Sunghyun Kim & Yunjong Wang, 2018. "RMB Bloc in East Asia: Too Early to Talk About It?," Asian Economic Papers, MIT Press, vol. 17(3), pages 31-48, Fall.

    Cited by:

    1. An, Jiyoun & Kim, Hyo Sang & Park, Bokyeong, 2024. "Do China's policy measures for RMB internationalization foster currency co-movements?," International Review of Economics & Finance, Elsevier, vol. 91(C), pages 1033-1050.
    2. Shekhar Hari Kumar & Vimal Balasubramaniam & Ila Patnaik & Ajay Shah, 2020. "Who cares about the Renminbi?," 2020 Papers pha1373, Job Market Papers.
    3. Liu, Tao & Wang, Xiaosong & Woo, Wing Thye, 2022. "The rise of Renminbi in Asia: Evidence from Network Analysis and SWIFT dataset," Journal of Asian Economics, Elsevier, vol. 78(C).

  6. Chang, Yoosoon & Choi, Yongok & Kim, Chang Sik & Miller, J. Isaac & Park, Joon Y., 2016. "Disentangling temporal patterns in elasticities: A functional coefficient panel analysis of electricity demand," Energy Economics, Elsevier, vol. 60(C), pages 232-243.
    See citations under working paper version above.
  7. Chang, Yoosoon & Kim, Chang Sik & Park, Joon Y., 2016. "Nonstationarity in time series of state densities," Journal of Econometrics, Elsevier, vol. 192(1), pages 152-167.

    Cited by:

    1. Beare, Brendan K. & Seo, Won-Ki, 2020. "Representation Of I(1) And I(2) Autoregressive Hilbertian Processes," Econometric Theory, Cambridge University Press, vol. 36(5), pages 773-802, October.
    2. Won-Ki Seo, 2020. "Functional Principal Component Analysis for Cointegrated Functional Time Series," Papers 2011.12781, arXiv.org, revised Apr 2023.
    3. Yoosoon Chang & Fabio Gómez-Rodríguez & Christian Matthes, 2023. "The Influence of Fiscal and Monetary Policies on the Shape of the Yield Curve," CAMA Working Papers 2023-65, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    4. Minsu Chang & Xiaohong Chen & Frank Schorfheide, 2021. "Heterogeneity and Aggregate Fluctuations," NBER Working Papers 28853, National Bureau of Economic Research, Inc.
    5. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
      • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
    6. Won‐Ki Seo, 2024. "Functional principal component analysis for cointegrated functional time series," Journal of Time Series Analysis, Wiley Blackwell, vol. 45(2), pages 320-330, March.
    7. Yoonseok Lee & Donggyu Sul, 2023. "Depth-weighted Forecast Combination: Application to COVID-19 Cases," Advances in Econometrics, in: Essays in Honor of Joon Y. Park: Econometric Methodology in Empirical Applications, volume 45, pages 235-260, Emerald Group Publishing Limited.
    8. Yoosoon Chang & Yongok Choi & Chang Sik Kim & J. Isaac Miller & Joon Y. Park, 2024. "Common Trends and Country Specific Heterogeneities in Long-Run World Energy Consumption," CAMA Working Papers 2024-04, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    9. Jin Seo Cho & Peter C. B. Phillips & Juwon Seo, 2019. "Parametric Inference on the Mean of Functional Data Applied to Lifetime Income Curves," Working papers 2019rwp-153, Yonsei University, Yonsei Economics Research Institute.
    10. Jin Seo Cho & Peter C. B. Phillips & Juwon Seo, 2022. "Parametric Conditional Mean Inference With Functional Data Applied To Lifetime Income Curves," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 63(1), pages 391-456, February.
    11. ARATA Yoshiyuki, 2017. "A Functional Linear Regression Model in the Space of Probability Density Functions," Discussion papers 17015, Research Institute of Economy, Trade and Industry (RIETI).
    12. Minsu Chang & Frank Schorfheide, 2024. "On the Effects of Monetary Policy Shocks on Income and Consumption Heterogeneity," PIER Working Paper Archive 24-003, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    13. Gadea Rivas, María Dolores & Gonzalo, Jesús, 2020. "Trends in distributional characteristics: Existence of global warming," Journal of Econometrics, Elsevier, vol. 214(1), pages 153-174.
    14. Yoosoon Chang & Robert K. Kaufmann & Chang Sik Kim & J. Isaac Miller & Joon Y. Park & Sungkeun Park, 2016. "Evaluating trends in time series of distributions: A spatial fingerprint of human effects on climate," Working Papers 1622, Department of Economics, University of Missouri, revised 17 Sep 2018.
    15. Morten {O}rregaard Nielsen & Won-Ki Seo & Dakyung Seong, 2023. "Inference on common trends in functional time series," Papers 2312.00590, arXiv.org, revised May 2024.
    16. María Dolores Gadea Rivas & Jesús Gonzalo, 2022. "A tale of three cities: climate heterogeneity," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 13(1), pages 475-511, May.
    17. Yoosoon Chang & Yongok Choi & Chang Sik Kim & J. Isaac Miller & Joon Y. Park, 2019. "Forecasting Regional Long-Run Energy Demand: A Functional Coefficient Panel Approach," Working Papers 1915, Department of Economics, University of Missouri.
    18. Nielsen, Morten Ørregaard & Seo, Won-Ki & Seong, Dakyung, 2023. "Inference On The Dimension Of The Nonstationary Subspace In Functional Time Series," Econometric Theory, Cambridge University Press, vol. 39(3), pages 443-480, June.
    19. Maria Dolores Gadea & Jesus Gonzalo, 2023. "Climate change heterogeneity: A new quantitative approach," Papers 2301.02648, arXiv.org.
    20. Christian Bayer & Luis Calderon & Moritz Kuhn, 2025. "Distributional Dynamics," CRC TR 224 Discussion Paper Series crctr224_2025_625, University of Bonn and University of Mannheim, Germany.
    21. Massimo Franchi & Paolo Paruolo, 2017. "Cointegration in functional autoregressive processes," DSS Empirical Economics and Econometrics Working Papers Series 2017/5, Centre for Empirical Economics and Econometrics, Department of Statistics, "Sapienza" University of Rome.
    22. Seo, Won-Ki & Beare, Brendan K., 2019. "Cointegrated linear processes in Bayes Hilbert space," Statistics & Probability Letters, Elsevier, vol. 147(C), pages 90-95.
    23. Brendan K. Beare, 2017. "The Chang-Kim-Park Model of Cointegrated Density-Valued Time Series Cannot Accommodate a Stochastic Trend," Econ Journal Watch, Econ Journal Watch, vol. 14(2), pages 133–137-1, May.
    24. Yoosoon Chang & Fabio Gómez-Rodríguez & Mr. Gee Hee Hong, 2022. "The Effects of Economic Shocks on Heterogeneous Inflation Expectations," IMF Working Papers 2022/132, International Monetary Fund.
    25. Salish, Nazarii & Gleim, Alexander, 2019. "A moment-based notion of time dependence for functional time series," Journal of Econometrics, Elsevier, vol. 212(2), pages 377-392.
    26. Yoosoon Chang & J. Isaac Miller & Joon K. Park, 2024. "Shocking Climate: Identifying Economic Damages from Anthropogenic and Natural Climate Change," CAEPR Working Papers 2024-007 Classification-E, Center for Applied Economics and Policy Research, Department of Economics, Indiana University Bloomington.
    27. Massimo Franchi & Iliyan Georgiev & Paolo Paruolo, 2024. "Canonical correlation analysis of stochastic trends via functional approximation," Papers 2411.19572, arXiv.org.
    28. Brendan K. Beare & Juwon Seo & Won-Ki Seo, 2017. "Cointegrated Linear Processes in Hilbert Space," Journal of Time Series Analysis, Wiley Blackwell, vol. 38(6), pages 1010-1027, November.
    29. Petersen, Alexander & Zhang, Chao & Kokoszka, Piotr, 2022. "Modeling Probability Density Functions as Data Objects," Econometrics and Statistics, Elsevier, vol. 21(C), pages 159-178.
    30. Christian Bayer & Luis Calderon & Moritz Kuhn, 2025. "Distributional Dynamics," ECONtribute Discussion Papers Series 351, University of Bonn and University of Cologne, Germany.

  8. Chang, Yoosoon & Kim, Chang Sik & Miller, J. Isaac & Park, Joon Y. & Park, Sungkeun, 2016. "A new approach to modeling the effects of temperature fluctuations on monthly electricity demand," Energy Economics, Elsevier, vol. 60(C), pages 206-216.
    See citations under working paper version above.
  9. Chang, Yoosoon & Kim, Chang Sik & Miller, J. Isaac & Park, Joon Y. & Park, Sungkeun, 2014. "Time-varying Long-run Income and Output Elasticities of Electricity Demand with an Application to Korea," Energy Economics, Elsevier, vol. 46(C), pages 334-347.

    Cited by:

    1. Yuo-Hsien Shiau & Su-Fen Yang & Rishan Adha & Syamsiyatul Muzayyanah, 2022. "Modeling Industrial Energy Demand in Relation to Subsector Manufacturing Output and Climate Change: Artificial Neural Network Insights," Sustainability, MDPI, vol. 14(5), pages 1-18, March.
    2. Hocheol Jeon, 2019. "The Impact of Climate Change on Passenger Vehicle Fuel Consumption: Evidence from U.S. Panel Data," Energies, MDPI, vol. 12(23), pages 1-15, November.
    3. Julián Pérez-García & Julián Moral-Carcedo, 2017. "Why Electricity Demand Is Highly Income-Elastic in Spain: A Cross-Country Comparison Based on an Index-Decomposition Analysis," Energies, MDPI, vol. 10(3), pages 1-20, March.
    4. Hyo-Jin Kim & Gyeong-Sam Kim & Seung-Hoon Yoo, 2019. "Demand Function for Industrial Electricity: Evidence from South Korean Manufacturing Sector," Sustainability, MDPI, vol. 11(18), pages 1-11, September.
    5. Kyungsik Nam, 2021. "Nonlinear Cointegrating Regression of the Earth’s Surface Mean Temperature Anomalies on Total Radiative Forcing," Econometrics, MDPI, vol. 9(1), pages 1-25, February.
    6. Daniel de Abreu Pereira Uhr & Júlia Gallego Ziero Uhr, André Luis Squarize Chagas, 2017. "Estimation of price and income elasticities for the Brazilian household electricity demand," Working Papers, Department of Economics 2017_12, University of São Paulo (FEA-USP).
    7. Kyungsik Nam & Sungro Lee & Hocheol Jeon, 2020. "Nonlinearity between CO 2 Emission and Economic Development: Evidence from a Functional Coefficient Panel Approach," Sustainability, MDPI, vol. 12(24), pages 1-10, December.
    8. Pereira Uhr, Daniel de Abreu & Squarize Chagas, André Luis & Ziero Uhr, Júlia Gallego, 2019. "Estimation of elasticities for electricity demand in Brazilian households and policy implications," Energy Policy, Elsevier, vol. 129(C), pages 69-79.
    9. Pérez-García, Julián & Moral-Carcedo, Julián, 2016. "Analysis and long term forecasting of electricity demand trough a decomposition model: A case study for Spain," Energy, Elsevier, vol. 97(C), pages 127-143.
    10. Yasunobu Wakashiro, 2019. "Estimating price elasticity of demand for electricity: the case of Japanese manufacturing industry," International Journal of Economic Policy Studies, Springer, vol. 13(1), pages 173-191, January.
    11. Polbin, Andrey & Skrobotov, Anton, 2022. "On decrease in oil price elasticity of GDP and investment in Russia," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 66, pages 5-24.
    12. Hyo-Jin Kim & Jae-Sung Paek & Seung-Hoon Yoo, 2019. "Price Elasticity of Heat Demand in South Korean Manufacturing Sector: An Empirical Investigation," Sustainability, MDPI, vol. 11(21), pages 1-10, November.
    13. Khan, Muhammad Arshad & Abbas, Faisal, 2016. "The dynamics of electricity demand in Pakistan: A panel cointegration analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 1159-1178.
    14. Ribó-Pérez, David & Van der Weijde, Adriaan H. & Álvarez-Bel, Carlos, 2019. "Effects of self-generation in imperfectly competitive electricity markets: The case of Spain," Energy Policy, Elsevier, vol. 133(C).
    15. Salisu, Afees A. & Ayinde, Taofeek O., 2016. "Modeling energy demand: Some emerging issues," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 1470-1480.
    16. Soon, Byung Min & Thompson, Wyatt, 2017. "Testing for Persistent Japanese Beef Trade Impacts from BSE Using a Time-Varying Armington Model," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 259150, Agricultural and Applied Economics Association.
    17. Yoosoon Chang & Chang Sik Kim & J. Isaac Miller & Joon Y. Park & Sungkeun Park, 2015. "A New Approach to Modeling the Effects of Temperature Fluctuations on Monthly Electricity Demand," Working Papers 1512, Department of Economics, University of Missouri.
    18. Jeyhun I. Mikayilov & Fakhri J. Hasanov & Carlo A. Bollino & Ceyhun Mahmudlu, 2017. "Modeling of Electricity Demand for Azerbaijan: Time-Varying Coefficient Cointegration Approach," Energies, MDPI, vol. 10(11), pages 1-12, November.
    19. Ozturk, Ilhan & Arisoy, Ibrahim, 2016. "An estimation of crude oil import demand in Turkey: Evidence from time-varying parameters approach," Energy Policy, Elsevier, vol. 99(C), pages 174-179.
    20. Jeyhun I. Mikayilov & Fakhri J. Hasanov & Marzio Galeotti, 2018. "Decoupling of C02 Emissions and GDP: A Time-Varying Cointegration Approach," IEFE Working Papers 101, IEFE, Center for Research on Energy and Environmental Economics and Policy, Universita' Bocconi, Milano, Italy.
    21. Nikos Sakkas & Sofia Yfanti & Costas Daskalakis & Eduard Barbu & Marharyta Domnich, 2021. "Interpretable Forecasting of Energy Demand in the Residential Sector," Energies, MDPI, vol. 14(20), pages 1-17, October.
    22. Kaneko, Nanae & Fujimoto, Yu & Kabe, Satoshi & Hayashida, Motonari & Hayashi, Yasuhiro, 2020. "Sparse modeling approach for identifying the dominant factors affecting situation-dependent hourly electricity demand," Applied Energy, Elsevier, vol. 265(C).
    23. Tan, Xiujie & Wang, Banban & Wei, Jie & Taghizadeh-Hesary, Farhad, 2023. "The role of carbon pricing in achieving energy transition in the Post-COP26 era: Evidence from China's industrial energy conservation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 182(C).
    24. Hortay, Olivér & Szőke, Tamás, 2019. "Keresleti árrugalmasság becslése a magyar villamosenergia-piacon [Estimating demand-price elasticity on the Hungarian electric energy market]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(7), pages 788-804.
    25. Wang, Banban & Wei, Jie & Tan, Xiujie & Su, Bin, 2021. "The sectorally heterogeneous and time-varying price elasticities of energy demand in China," Energy Economics, Elsevier, vol. 102(C).
    26. Aslam, Misbah & Ahmad, Eatzaz, 2023. "Untangling electricity demand elasticities: Insights from heterogeneous household groups in Pakistan," Energy, Elsevier, vol. 282(C).
    27. Jeyhun Mikayilov & Fred Joutz & Fakhri Hasanov, 2019. "Gasoline Demand in Saudi Arabia: Are the Price and Income Elasticities Constant?," Discussion Papers ks--2019-dp81, King Abdullah Petroleum Studies and Research Center.
    28. Jeyhun I. Mikayilov & Shahriyar Mukhtarov & Jeyhun Mammadov, 2020. "Gasoline Demand Elasticities at the Backdrop of Lower Oil Prices: Fuel-Subsidizing Country Case," Energies, MDPI, vol. 13(24), pages 1-18, December.
    29. Liddle, Brantley, 2023. "Is timing everything? Assessing the evidence on whether energy/electricity demand elasticities are time-varying," Energy Economics, Elsevier, vol. 124(C).
    30. Asuamah Yeboah, Samuel, 2018. "Do government activities determine electricity consumption in Ghana? An empirical investigation," MPRA Paper 89408, University Library of Munich, Germany.
    31. Yoosoon Chang & Yongok Choi & Chang Sik Kim & Joon Y. Park & J. Isaac Miller, 2013. "Disentangling Temporal Patterns in Elasticities: A Functional Coefficient Panel Analysis of Electricity Demand," Working Papers 1320, Department of Economics, University of Missouri.
    32. Ha-Hyun Jo & Minwoo Jang & Jaehyeok Kim, 2020. "How Population Age Distribution Affects Future Electricity Demand in Korea: Applying Population Polynomial Function," Energies, MDPI, vol. 13(20), pages 1-17, October.
    33. Sharimakin, Akinsehinwa, 2021. "Modelling asymmetric price responses of industrial energy demand with a dynamic hierarchical model," Energy Economics, Elsevier, vol. 98(C).
    34. Fukushige, Mototsugu & Yamawaki, Hiroshige, 2015. "The relationship between an electricity supply ceiling and economic growth: An application of disequilibrium modeling to Taiwan," Journal of Asian Economics, Elsevier, vol. 36(C), pages 14-23.
    35. Liddle, Brantley & Smyth, Russell & Zhang, Xibin, 2020. "Time-varying income and price elasticities for energy demand: Evidence from a middle-income panel," Energy Economics, Elsevier, vol. 86(C).
    36. Jang, Heesun & Moon, Seongman & Kim, Jihyo, 2024. "Effects of time-of-use pricing for residential customers and wholesale market consequences in South Korea," Energy Economics, Elsevier, vol. 134(C).
    37. Martin Falk & Xiang Lin, 2018. "Income elasticity of overnight stays over seven decades," Tourism Economics, , vol. 24(8), pages 1015-1028, December.
    38. Agnolucci, Paolo & De Lipsis, Vincenzo & Arvanitopoulos, Theodoros, 2017. "Modelling UK sub-sector industrial energy demand," Energy Economics, Elsevier, vol. 67(C), pages 366-374.
    39. Keita Honjo & Hiroto Shiraki & Shuichi Ashina, 2018. "Dynamic linear modeling of monthly electricity demand in Japan: Time variation of electricity conservation effect," PLOS ONE, Public Library of Science, vol. 13(4), pages 1-23, April.
    40. Wang, Nan & Mogi, Gento, 2017. "Industrial and residential electricity demand dynamics in Japan: How did price and income elasticities evolve from 1989 to 2014?," Energy Policy, Elsevier, vol. 106(C), pages 233-243.
    41. Daniel Morais de Souza & Rogerio Silva de Mattos & Alexandre Zanini, 2022. "Estimating Elasticities for the Residential Demand of Electricity in Brazil Using Cointegration Models," International Journal of Energy Economics and Policy, Econjournals, vol. 12(2), pages 315-324, March.
    42. Joo, Young C. & Park, Sung Y., 2017. "Oil prices and stock markets: Does the effect of uncertainty change over time?," Energy Economics, Elsevier, vol. 61(C), pages 42-51.
    43. Chang Sik Kim & Sunghyun Kim & Yunjong Wang, 2018. "RMB Bloc in East Asia: Too Early to Talk About It?," Asian Economic Papers, MIT Press, vol. 17(3), pages 31-48, Fall.

  10. Kim, Chang Sik & Kim, In-Moo, 2012. "Partial parametric estimation for nonstationary nonlinear regressions," Journal of Econometrics, Elsevier, vol. 167(2), pages 448-457.

    Cited by:

    1. Hu, Zhishui & Phillips, Peter C.B. & Wang, Qiying, 2021. "Nonlinear Cointegrating Power Function Regression With Endogeneity," Econometric Theory, Cambridge University Press, vol. 37(6), pages 1173-1213, December.

  11. Chang Sik Kim & Joon Park, 2010. "Cointegrating Regressions with Time Heterogeneity," Econometric Reviews, Taylor & Francis Journals, vol. 29(4), pages 397-438.

    Cited by:

    1. Angeliki Papana & Catherine Kyrtsou & Dimitris Kugiumtzis & Cees Diks, 2016. "Detecting Causality in Non-stationary Time Series Using Partial Symbolic Transfer Entropy: Evidence in Financial Data," Computational Economics, Springer;Society for Computational Economics, vol. 47(3), pages 341-365, March.
    2. Valentin Patilea & Hamdi Raïssi, 2014. "Testing Second-Order Dynamics for Autoregressive Processes in Presence of Time-Varying Variance," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 109(507), pages 1099-1111, September.
    3. Quentin Giai Gianetto & Hamdi Raïssi, 2015. "Testing Instantaneous Causality in Presence of Nonconstant Unconditional Covariance," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 33(1), pages 46-53, January.
    4. Hirukawa, Junichi & Raïssi, Hamdi, 2020. "Testing linear relationships between non-constant variances of economic variables," Economic Modelling, Elsevier, vol. 90(C), pages 182-189.
    5. Papana, A. & Kyrtsou, K. & Kugiumtzis, D. & Diks, C.G.H., 2013. "Partial Symbolic Transfer Entropy," CeNDEF Working Papers 13-16, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    6. Kim, Chang Sik & Kim, In-Moo, 2012. "Partial parametric estimation for nonstationary nonlinear regressions," Journal of Econometrics, Elsevier, vol. 167(2), pages 448-457.

  12. Soobin Kim & Chang Sik Kim, 2010. "Do S&P 500 and KOSPI Move Together?: A Functional Regression Approach," Korean Economic Review, Korean Economic Association, vol. 26, pages 401-430.

    Cited by:

    1. Ahmed, Walid M.A., 2022. "On the higher-order moment interdependence of stock and commodity markets: A wavelet coherence analysis," The Quarterly Review of Economics and Finance, Elsevier, vol. 83(C), pages 135-151.

  13. Kim Chang Sik, 2009. "Test for Spatial Dominances in the Distribution of Stock Returns: Evidence from the Korean Stock Market Before and After the East Asian Financial Crisis," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 13(4), pages 1-27, September.

    Cited by:

    1. Eunhee Lee & Chang Kim & In-Moo Kim, 2015. "Equity premium over different investment horizons," Empirical Economics, Springer, vol. 48(3), pages 1169-1187, May.
    2. Ibarra, Raul, 2013. "A spatial dominance approach to evaluate the performance of stocks and bonds: Does the investment horizon matter?," The Quarterly Review of Economics and Finance, Elsevier, vol. 53(4), pages 429-439.
    3. Sungro Lee, Chang Sik Kim, In-Moo Kim & Chang Sik Kim & In-Moo Kim, 2012. "Testing the Monday Effect using High-frequency Intraday Returns: A Spatial Dominance Approach," Korean Economic Review, Korean Economic Association, vol. 28, pages 69-90.

  14. Phillips, Peter C.B. & Kim, Chang Sik, 2007. "Long-Run Covariance Matrices For Fractionally Integrated Processes," Econometric Theory, Cambridge University Press, vol. 23(6), pages 1233-1247, December.
    See citations under working paper version above.
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