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Anandamayee Majumdar

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. Rangan Gupta & Anandamayee Majumdar & Jacobus Nel & Sowmya Subramaniam, 2021. "Geopolitical Risks and the High-Frequency Movements of the US Term Structure of Interest Rates," Working Papers 202150, University of Pretoria, Department of Economics.

    Cited by:

    1. Rangan Gupta & Sayar Karmakar & Christian Pierdzioch, 2022. "Safe Havens, Machine Learning, and the Sources of Geopolitical Risk: A Forecasting Analysis Using Over a Century of Data," Working Papers 202201, University of Pretoria, Department of Economics.

  2. Elie Bouri & Rangan Gupta & Anandamayee Majumdar & Sowmya Subramaniam, 2020. "Time-Varying Risk Aversion and Forecastability of the US Term Structure of Interest Rates," Working Papers 202098, University of Pretoria, Department of Economics.

    Cited by:

    1. Xu, Xin & Xu, Xiaoguang, 2023. "Monetary policy transmission modeling and policy responses," The North American Journal of Economics and Finance, Elsevier, vol. 64(C).

  3. Tsangyao Chang & Rangan Gupta & Anandamayee Majumdar & Christian Pierdzioch, 2017. "Predicting Stock Market Movements with a Time-Varying Consumption-Aggregate Wealth Ratio," Working Papers 201756, University of Pretoria, Department of Economics.

    Cited by:

    1. Rangan Gupta & Hardik A. Marfatia & Eric Olson, 2019. "Effect of Uncertainty on U.S. Stock Returns and Volatility: Evidence from Over Eighty Years of High-Frequency Data," Working Papers 201942, University of Pretoria, Department of Economics.
    2. Hui Hong & Zhicun Bian & Chien-Chiang Lee, 2021. "COVID-19 and instability of stock market performance: evidence from the U.S," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-18, December.
    3. Balcilar, Mehmet & Gupta, Rangan & Sousa, Ricardo M. & Wohar, Mark E., 2021. "Linking U.S. State-level housing market returns, and the consumption-(Dis)Aggregate wealth ratio," International Review of Economics & Finance, Elsevier, vol. 71(C), pages 779-810.
    4. Marina Kolosnitsyna & Anna Philippova, 2017. "Family Benefits and Poverty: The Case of Russia," HSE Working papers WP BRP 03/PSP/2017, National Research University Higher School of Economics.
    5. Oğuzhan Çepni & Rangan Gupta & Mark E. Wohar, 2021. "Variants of consumption‐wealth ratios and predictability of U.S. government bond risk premia," International Review of Finance, International Review of Finance Ltd., vol. 21(2), pages 661-674, June.
    6. Oguzhan Cepni & Rangan Gupta & Mark E. Wohar, 2019. "Variants of Consumption-Wealth Ratios and Predictability of U.S. Government Bond Risk Premia: Old is still Gold," Working Papers 201912, University of Pretoria, Department of Economics.

  4. Rangan Gupta & Anandamayee Majumdar & Mark Wohar, 2016. "The Role of Current Account Balance in Forecasting the US Equity Premium: Evidence from a Quantile Predictive Regression Approach," Working Papers 201612, University of Pretoria, Department of Economics.

    Cited by:

    1. Rangan Gupta & Patrick Kanda & Mark E. Wohar, 2021. "Predicting Stock Market Movements in the United States: The Role of Presidential Approval Ratings," International Review of Finance, International Review of Finance Ltd., vol. 21(1), pages 324-335, March.
    2. Mehmet Balcilar & Rangan Gupta & Christian Pierdzioch, 2022. "Oil-Price Uncertainty and International Stock Returns: Dissecting Quantile-Based Predictability and Spillover Effects Using More than a Century of Data," Energies, MDPI, vol. 15(22), pages 1-26, November.
    3. Rangan Gupta & Christian Pierdzioch, 2023. "Do U.S. economic conditions at the state level predict the realized volatility of oil-price returns? A quantile machine-learning approach," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-22, December.
    4. Afees A. Salisu & Rangan Gupta, 2021. "Commodity Prices and Forecastability of South African Stock Returns Over a Century: Sentiments versus Fundamentals," Working Papers 202144, University of Pretoria, Department of Economics.
    5. Gupta, Rangan & Huber, Florian & Piribauer, Philipp, 2020. "Predicting international equity returns: Evidence from time-varying parameter vector autoregressive models," International Review of Financial Analysis, Elsevier, vol. 68(C).
    6. Mehmet Balcilar & David Gabauer & Rangan Gupta & Christian Pierdzioch, 2021. "Climate Risks and Forecasting Stock-Market Returns in Advanced Economies Over a Century," Working Papers 202183, University of Pretoria, Department of Economics.
    7. Gupta, Rangan & Ji, Qiang & Pierdzioch, Christian & Plakandaras, Vasilios, 2023. "Forecasting the conditional distribution of realized volatility of oil price returns: The role of skewness over 1859 to 2023," Finance Research Letters, Elsevier, vol. 58(PC).
    8. Afees A. Salisu & Rangan Gupta & Ahamuefula E. Ogbonna, 2023. "Tail risks and forecastability of stock returns of advanced economies: evidence from centuries of data," The European Journal of Finance, Taylor & Francis Journals, vol. 29(4), pages 466-481, March.

  5. Rangan Gupta & Anandamayee Majumdar & Christian Pierdzioch & Mark Wohar, 2016. "Do Terror Attacks Predict Gold Returns? Evidence from a Quantile-Predictive-Regression Approach," Working Papers 201626, University of Pretoria, Department of Economics.

    Cited by:

    1. Chen, Guojin & Liu, Yanzhen & Zhang, Yu, 2020. "Can systemic risk measures predict economic shocks? Evidence from China," China Economic Review, Elsevier, vol. 64(C).
    2. Jamal Bouoiyour & Refk Selmi & Shawkat Hammoudeh & Mark E Wohar, 2019. "What are the categories of geopolitical risks that could drive oil prices higher? Acts or threats?," Post-Print hal-02409062, HAL.
    3. Mehmet Balcilar & Matteo Bonato & Riza Demirer & Rangan Gupta, 2016. "Geopolitical Risks and Stock Market Dynamics of the BRICS," Working Papers 201648, University of Pretoria, Department of Economics.
    4. Chen, Zhuoyi & Liu, Yuanyuan & Zhang, Hongwei, 2024. "Can geopolitical risks impact the long-run correlation between crude oil and clean energy markets? Evidence from a regime-switching analysis," Renewable Energy, Elsevier, vol. 229(C).
    5. Cepni, Oguzhan & Emirmahmutoglu, Furkan & Guney, Ibrahim Ethem & Yilmaz, Muhammed Hasan, 2023. "Do the carry trades respond to geopolitical risks? Evidence from BRICS countries," Economic Systems, Elsevier, vol. 47(2).
    6. Elie Bouri & Riza Demirer & Rangan Gupta & Hardik A. Marfatia, 2017. "Geopolitical Risks and Movements in Islamic Bond and Equity Markets: A Note," Working Papers 201743, University of Pretoria, Department of Economics.
    7. Christos Bouras & Christina Christou & Rangan Gupta & Tahir Suleman, 2020. "Geopolitical Risks, Returns, and Volatility in Emerging Stock Markets: Evidence from a Panel GARCH Model," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 55(8), pages 1841-1856, July.
    8. Liu, Yang & Han, Liyan & Xu, Yang, 2021. "The impact of geopolitical uncertainty on energy volatility," International Review of Financial Analysis, Elsevier, vol. 75(C).
    9. Yilanci, Veli & Kilci, Esra N., 2021. "The role of economic policy uncertainty and geopolitical risk in predicting prices of precious metals: Evidence from a time-varying bootstrap causality test," Resources Policy, Elsevier, vol. 72(C).
    10. Plakandaras, Vasilios & Ji, Qiang, 2022. "Intrinsic decompositions in gold forecasting," Journal of Commodity Markets, Elsevier, vol. 28(C).
    11. Nicholas Apergis & Matteo Bonato & Rangan Gupta & Clement Kyei, 2016. "Does Geopolitical Risks Predict Stock Returns and Volatility of Leading Defense Companies? Evidence from a Nonparametric Approach," Working Papers 201671, University of Pretoria, Department of Economics.
    12. Dichtl, Hubert, 2020. "Forecasting excess returns of the gold market: Can we learn from stock market predictions?," Journal of Commodity Markets, Elsevier, vol. 19(C).
    13. Rangan Gupta & Sayar Karmakar & Christian Pierdzioch, 2022. "Safe Havens, Machine Learning, and the Sources of Geopolitical Risk: A Forecasting Analysis Using Over a Century of Data," Working Papers 202201, University of Pretoria, Department of Economics.
    14. David Gabauer & Rangan Gupta & Sayar Karmakar & Joshua Nielsen, 2022. "Stock Market Bubbles and the Forecastability of Gold Returns (and Volatility)," Working Papers 202228, University of Pretoria, Department of Economics.
    15. Gupta, Rangan & Pierdzioch, Christian & Vivian, Andrew J. & Wohar, Mark E., 2019. "The predictive value of inequality measures for stock returns: An analysis of long-span UK data using quantile random forests," Finance Research Letters, Elsevier, vol. 29(C), pages 315-322.
    16. Chen, Jinyu & Huang, Yuxin & Ren, Xiaohang & Qu, Jingxiao, 2022. "Time-varying spillovers between trade policy uncertainty and precious metal markets: Evidence from China-US trade conflict," Resources Policy, Elsevier, vol. 76(C).
    17. Salisu, Afees A. & Gupta, Rangan & Nel, Jacobus & Bouri, Elie, 2022. "The (Asymmetric) effect of El Niño and La Niña on gold and silver prices in a GVAR model," Resources Policy, Elsevier, vol. 78(C).
    18. Song, Yu & Song, Yanqiu & Chang, Shiwei & He, Lele, 2024. "The role of gold in terrorism: Risk aversion or financing source?," Resources Policy, Elsevier, vol. 95(C).
    19. Demirer, Riza & Pierdzioch, Christian & Zhang, Huacheng, 2017. "On the short-term predictability of stock returns: A quantile boosting approach," Finance Research Letters, Elsevier, vol. 22(C), pages 35-41.
    20. Shahzad, Syed Jawad Hussain & Rahman, Md Lutfur & Lucey, Brian M. & Uddin, Gazi Salah, 2021. "Re-examining the real option characteristics of gold for gold mining companies," Resources Policy, Elsevier, vol. 70(C).
    21. Cheng, Sheng & Han, Lingyu & Cao, Yan & Jiang, Qisheng & Liang, Ruibin, 2022. "Gold-oil dynamic relationship and the asymmetric role of geopolitical risks: Evidence from Bayesian pdBEKK-GARCH with regime switching," Resources Policy, Elsevier, vol. 78(C).
    22. Li, Sufang & Tu, Dalun & Zeng, Yan & Gong, Chenggang & Yuan, Di, 2022. "Does geopolitical risk matter in crude oil and stock markets? Evidence from disaggregated data," Energy Economics, Elsevier, vol. 113(C).
    23. Mazhar Ummad, 2019. "Terrorism and Firm Performance: Empirical Evidence from Pakistan," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 19(1), pages 1-17, January.
    24. Christian Pierdzioch & Marian Risse, 2020. "Forecasting precious metal returns with multivariate random forests," Empirical Economics, Springer, vol. 58(3), pages 1167-1184, March.

  6. Mehmet Balcilar & Rangan Gupta & Renee van Eyden & Kirsten Thompson & Anandamayee Majumdar, 2015. "Comparing the Forecasting Ability of Financial Conditions Indices: The Case of South Africa," Working Papers 201517, University of Pretoria, Department of Economics.

    Cited by:

    1. Nima Nonejad, 2021. "An Overview Of Dynamic Model Averaging Techniques In Time‐Series Econometrics," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 566-614, April.
    2. Balcilar, Mehmet & Ozdemir, Zeynel Abidin & Ozdemir, Huseyin & Wohar, Mark E., 2020. "Fed’s unconventional monetary policy and risk spillover in the US financial markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 78(C), pages 42-52.
    3. Balcilar, Mehmet & Roubaud, David & Usman, Ojonugwa & Wohar, Mark E., 2021. "Moving out of the linear rut: A period-specific and regime-dependent exchange rate and oil price pass-through in the BRICS countries," Energy Economics, Elsevier, vol. 98(C).
    4. Mehmet Balcilar & David Roubaud & Ojonugwa Usman & Mark E. Wohar, 2019. "Testing the Asymmetric Effects of Exchange Rate and Oil Price Pass-Through in BRICS Countries: Does the state of the economy matter?," Working Papers 15-49, Eastern Mediterranean University, Department of Economics.
    5. Mehmet Balcilar & David Roubaud & Ojonugwa Usman & Mark E. Wohar, 2021. "Testing the asymmetric effects of exchange rate pass‐through in BRICS countries: Does the state of the economy matter?," The World Economy, Wiley Blackwell, vol. 44(1), pages 188-233, January.
    6. Adél Bosch & Steven F. Koch, 2020. "The South African Financial Cycle and its Relation to Household Deleveraging," South African Journal of Economics, Economic Society of South Africa, vol. 88(2), pages 145-173, June.
    7. Kaelo Ntwaepelo & Grivas Chiyaba, 2022. "Financial Stability Surveillance Tools: Evaluating the Performance of Stress Indices," Economics Discussion Papers em-dp2022-06, Department of Economics, University of Reading.
    8. Lulu Yang & Yankai Gai & An Zhang & Lihui Wang, 2024. "Analysis of the Impact of U.S. Trade Policy Uncertainty on China’s Grain Trade," Sustainability, MDPI, vol. 16(11), pages 1-23, May.
    9. Manamani SAHOO, 2017. "Financial conditions index (FCI), inflation and growth: Some evidence," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania / Editura Economica, vol. 0(3(612), A), pages 147-172, Autumn.

  7. Stelios Bekiros & Rangan Gupta & Anandamayee Majumdar, 2015. "Incorporating Economic Policy Uncertainty in US Equity Premium Models: A Nonlinear Predictability Analysis," Working Papers 201545, University of Pretoria, Department of Economics.

    Cited by:

    1. Assaf, Ata & Charif, Husni & Mokni, Khaled, 2021. "Dynamic connectedness between uncertainty and energy markets: Do investor sentiments matter?," Resources Policy, Elsevier, vol. 72(C).
    2. Bulent Diclehan Cadirci & Mustafa Tekdere, 2022. "The Effect of Economic Uncertainty on the Tax Wedge: The Case of Selected OECD Countries," Istanbul Journal of Economics-Istanbul Iktisat Dergisi, Istanbul University, Faculty of Economics, vol. 72(72-2), pages 787-822, December.
    3. Ming Fang & Chiu-Lan Chang, 2022. "Nexus between fiscal imbalances, green fiscal spending, and green economic growth: empirical findings from E-7 economies," Economic Change and Restructuring, Springer, vol. 55(4), pages 2423-2443, November.
    4. Mehmet Balcilar & Riza Demirer & Rangan Gupta & Mark E. Wohar, 2016. "Differences of Opinion and Stock Market Volatility: Evidence from a Nonparametric Causality-in-Quantiles Approach," Working Papers 201668, University of Pretoria, Department of Economics.
    5. Balcilar, Mehmet & Bouri, Elie & Gupta, Rangan & Roubaud, David, 2017. "Can volume predict Bitcoin returns and volatility? A quantiles-based approach," Economic Modelling, Elsevier, vol. 64(C), pages 74-81.
    6. Shabir, Mohsin & Jiang, Ping & Hashmi, Shujahat Haider & Bakhsh, Satar, 2022. "Non-linear nexus between economic policy uncertainty and bank lending," International Review of Economics & Finance, Elsevier, vol. 79(C), pages 657-679.
    7. Arshian Sharif & Subhan Ullah & Muhammad Shahbaz & Mantu Kumar Mahalik, 2021. "Sustainable tourism development and globalization: Recent insights from the United States," Sustainable Development, John Wiley & Sons, Ltd., vol. 29(5), pages 957-973, September.
    8. Mehmet Balcilar & Rangan Gupta & Christian Pierdzioch, 2022. "Oil-Price Uncertainty and International Stock Returns: Dissecting Quantile-Based Predictability and Spillover Effects Using More than a Century of Data," Energies, MDPI, vol. 15(22), pages 1-26, November.
    9. Chen, Wen-Yi & Chen, Mei-Ping, 2022. "Twitter’s daily happiness sentiment, economic policy uncertainty, and stock index fluctuations," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    10. Christou, Christina & Gupta, Rangan, 2020. "Forecasting equity premium in a panel of OECD countries: The role of economic policy uncertainty," The Quarterly Review of Economics and Finance, Elsevier, vol. 76(C), pages 243-248.
    11. Cakici, Nusret & Shahzad, Syed Jawad Hussain & Będowska-Sójka, Barbara & Zaremba, Adam, 2024. "Machine learning and the cross-section of cryptocurrency returns," International Review of Financial Analysis, Elsevier, vol. 94(C).
    12. Mehmet Balcilar & Matteo Bonato & Riza Demirer & Rangan Gupta, 2016. "Geopolitical Risks and Stock Market Dynamics of the BRICS," Working Papers 201648, University of Pretoria, Department of Economics.
    13. Rangan Gupta & Marian Risse & David A. Volkman & Mark E. Wohar, 2017. "The Role of Term Spread and Pattern Changes in Predicting Stock Returns and Volatility of the United Kingdom: Evidence from a Nonparametric Causality-in-Quantiles Test Using Over 250 Years of Data," Working Papers 201755, University of Pretoria, Department of Economics.
    14. Giray Gozgor & Ender Demir, 2017. "Excess stock returns, oil shocks, and policy uncertainty in the U.S," Economics Bulletin, AccessEcon, vol. 37(2), pages 741-755.
    15. Nonejad, Nima, 2022. "Predicting equity premium out-of-sample by conditioning on newspaper-based uncertainty measures: A comparative study," International Review of Financial Analysis, Elsevier, vol. 83(C).
    16. Rehman, Mobeen Ur, 2018. "Do oil shocks predict economic policy uncertainty?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 498(C), pages 123-136.
    17. Kang, Wensheng & de Gracia, Fernando Perez & Ratti, Ronald A., 2019. "The asymmetric response of gasoline prices to oil price shocks and policy uncertainty," Energy Economics, Elsevier, vol. 77(C), pages 66-79.
    18. Jun Wen & Samia Khalid & Hamid Mahmood & Xiuyun Yang, 2022. "Economic policy uncertainty and growth nexus in Pakistan: a new evidence using NARDL model," Economic Change and Restructuring, Springer, vol. 55(3), pages 1701-1715, August.
    19. Badshah, Ihsan & Demirer, Riza & Suleman, Muhammad Tahir, 2019. "The effect of economic policy uncertainty on stock-commodity correlations and its implications on optimal hedging," Energy Economics, Elsevier, vol. 84(C).
    20. Basher, Syed Abul & Haug, Alfred A. & Sadorsky, Perry, 2019. "The impact of economic policy uncertainty and commodity prices on CARB country stock market volatility," MPRA Paper 96577, University Library of Munich, Germany.
    21. Song, Lu & Tian, Gengyu & Jiang, Yonghong, 2022. "Connectedness of commodity, exchange rate and categorical economic policy uncertainties — Evidence from China," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
    22. Zhao, Linhai & Chau, Ka Yin & Tran, Trung Kien & Sadiq, Muhammad & Xuyen, Nguyen Thi My & Phan, Thi Thu Hien, 2022. "Enhancing green economic recovery through green bonds financing and energy efficiency investments," Economic Analysis and Policy, Elsevier, vol. 76(C), pages 488-501.
    23. Alqahtani, Abdullah & Klein, Tony, 2021. "Oil price changes, uncertainty, and geopolitical risks: On the resilience of GCC countries to global tensions," Energy, Elsevier, vol. 236(C).
    24. Golab, Anna & Bannigidadmath, Deepa & Pham, Thach Ngoc & Thuraisamy, Kannan, 2022. "Economic policy uncertainty and industry return predictability – Evidence from the UK," International Review of Economics & Finance, Elsevier, vol. 82(C), pages 433-447.
    25. Gupta, Rangan & Huber, Florian & Piribauer, Philipp, 2020. "Predicting international equity returns: Evidence from time-varying parameter vector autoregressive models," International Review of Financial Analysis, Elsevier, vol. 68(C).
    26. Salokhiddin Avazkhodjaev & Nont Dhiensiri & Farkhod Mukhamedov, 2024. "Does Green Energy Investment Effects on Islamic and Conventional Stock Markets? New Evidence from Advanced Economies," International Journal of Energy Economics and Policy, Econjournals, vol. 14(1), pages 592-602, January.
    27. Tahir Suleman & Rangan Gupta & Mehmet Balcilar, 2016. "Does Country Risks Predict Stock Returns and Volatility? Evidence from a Nonparametric Approach," Working Papers 201675, University of Pretoria, Department of Economics.
    28. Nicholas Apergis & Tasawar Hayat & Tareq Saeed, 2021. "Cyclicality of commodity markets with respect to the U.S. economic policy uncertainty based on granger causality in quantiles," Economic Notes, Banca Monte dei Paschi di Siena SpA, vol. 50(1), February.
    29. Zeng, Qing & Lu, Xinjie & Dong, Dayong & Li, Pan, 2022. "Category-specific EPU indices, macroeconomic variables and stock market return predictability," International Review of Financial Analysis, Elsevier, vol. 84(C).
    30. Helseth, Marius Aleksander Emblem & Krakstad, Svein Olav & Molnár, Peter & Norlin, Karl-Martin, 2020. "Can policy and financial risk predict stock markets?," Journal of Economic Behavior & Organization, Elsevier, vol. 176(C), pages 701-719.
    31. Tsai, I-Chun, 2018. "Flash crash and policy uncertainty," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 57(C), pages 248-260.
    32. Huang, Wei-Ling & Lin, Wen-Yuan & Ning, Shao-Lin, 2020. "The effect of economic policy uncertainty on China’s housing market," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).
    33. Yu, Honghai & Fang, Libing & Du, Donglei & Yan, Panpan, 2017. "How EPU drives long-term industry beta," Finance Research Letters, Elsevier, vol. 22(C), pages 249-258.
    34. Nicholas Apergis & Matteo Bonato & Rangan Gupta & Clement Kyei, 2016. "Does Geopolitical Risks Predict Stock Returns and Volatility of Leading Defense Companies? Evidence from a Nonparametric Approach," Working Papers 201671, University of Pretoria, Department of Economics.
    35. Salisu, Afees A. & Shaik, Muneer, 2022. "Islamic Stock indices and COVID-19 pandemic," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 282-293.
    36. Hong, Yun & Zhang, Rushan & Zhang, Feipeng, 2024. "Time-varying causality impact of economic policy uncertainty on stock market returns: Global evidence from developed and emerging countries," International Review of Financial Analysis, Elsevier, vol. 91(C).
    37. Yonghong Jiang & Gengyu Tian & Yiqi Wu & Bin Mo, 2022. "Impacts of geopolitical risks and economic policy uncertainty on Chinese tourism‐listed company stock," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 320-333, January.
    38. Nonejad, Nima, 2021. "Predicting equity premium using news-based economic policy uncertainty: Not all uncertainty changes are equally important," International Review of Financial Analysis, Elsevier, vol. 77(C).
    39. Hu, Zinan & Borjigin, Sumuya, 2024. "The amplifying role of geopolitical Risks, economic policy Uncertainty, and climate risks on Energy-Stock market volatility spillover across economic cycles," The North American Journal of Economics and Finance, Elsevier, vol. 71(C).
    40. Li, Dakai & Zhang, Fan & Li, Xuezhi, 2022. "Can U.S. trade policy uncertainty help in predicting stock market excess return?," Finance Research Letters, Elsevier, vol. 49(C).
    41. Matthew W. Clance & Giray Gozgor & Rangan Gupta & Chi Keung Marco Lau, 2019. "The Relationship between Economic Uncertainty and Corporate Tax Rates," Working Papers 201945, University of Pretoria, Department of Economics.
    42. Rehman, Mobeen Ur & Kang, Sang Hoon, 2021. "A time–frequency comovement and causality relationship between Bitcoin hashrate and energy commodity markets," Global Finance Journal, Elsevier, vol. 49(C).
    43. Mehmet Balcilar & Elie Bouri & Rangan Gupta & David Roubaud, 2016. "Can Volume Predict Bitcoin Returns and Volatility? A Nonparametric Causality-in-Quantiles Approach," Working Papers 201662, University of Pretoria, Department of Economics.
    44. Rangan Gupta & Anandamayee Majumdar & Mark E. Wohar, 2017. "The Role of Current Account Balance in Forecasting the US Equity Premium: Evidence From a Quantile Predictive Regression Approach," Open Economies Review, Springer, vol. 28(1), pages 47-59, February.
    45. Salokhiddin Avazkhodjaev & Jaloliddin Usmonov & M ria Bohdalov & Wee-Yeap Lau, 2022. "The Causal Nexus between Renewable Energy, CO2 Emissions, and Economic Growth: New Evidence from CIS Countries," International Journal of Energy Economics and Policy, Econjournals, vol. 12(6), pages 248-260, November.
    46. Lee, Chi-Chuan & Lee, Chien-Chiang & Li, Yong-Yi, 2021. "Oil price shocks, geopolitical risks, and green bond market dynamics," The North American Journal of Economics and Finance, Elsevier, vol. 55(C).
    47. Mishra, Shekhar & Sharif, Arshian & Khuntia, Sashikanta & Meo, Muhammad Saeed & Rehman Khan, Syed Abdul, 2019. "Does oil prices impede Islamic stock indices? Fresh insights from wavelet-based quantile-on-quantile approach," Resources Policy, Elsevier, vol. 62(C), pages 292-304.
    48. Rangan Gupta & John W. Muteba Mwamba & Mark E. Wohar, 2016. "The Role of Partisan Conflict in Forecasting the U.S. Equity Premium: A Nonparametric Approach," Working Papers 201686, University of Pretoria, Department of Economics.
    49. Helena Chuliá & Rangan Gupta & Jorge M. Uribe & Mark E. Wohar, 2016. "Impact of US Uncertainties on Emerging and Mature Markets: Evidence from a Quantile-Vector Autoregressive Approach," Working Papers 201656, University of Pretoria, Department of Economics.
    50. Salokhiddin Avazkhodjaev & Farkhod Mukhamedov & Jaloliddin Usmonov, 2022. "Do Energy and Gold Markets Interact with Islamic Stocks? Evidence from the Asia-Pacific Markets," International Journal of Energy Economics and Policy, Econjournals, vol. 12(3), pages 197-208, May.
    51. Lee, Chi-Chuan & Lee, Chien-Chiang, 2020. "Insurance activity, real output, and geopolitical risk: Fresh evidence from BRICS," Economic Modelling, Elsevier, vol. 92(C), pages 207-215.
    52. Mehmet Balcilar & Esin Cakan & Rangan Gupta, 2016. "Does U.S. News Impact Asian Emerging Markets? Evidence from Nonparametric Causality-in-Quantiles Test," Working Papers 201631, University of Pretoria, Department of Economics.
    53. Mohammad Arashi & Mohammad Mahdi Rounaghi, 2022. "Analysis of market efficiency and fractal feature of NASDAQ stock exchange: Time series modeling and forecasting of stock index using ARMA-GARCH model," Future Business Journal, Springer, vol. 8(1), pages 1-12, December.
    54. Mudassar Hasan & Muhammad Abubakr Naeem & Muhammad Arif & Syed Jawad Hussain Shahzad & Safwan Mohd Nor, 2020. "Geopolitical Risk and Tourism Stocks of Emerging Economies," Sustainability, MDPI, vol. 12(21), pages 1-21, November.
    55. Gu, Rongbao & Liu, Shengnan, 2022. "Nonlinear analysis of economic policy uncertainty: Based on the data in China, the US and the global," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 593(C).
    56. Godil, Danish Iqbal & Sarwat, Salman & Sharif, Arshian & Jermsittiparsert, Kittisak, 2020. "How oil prices, gold prices, uncertainty and risk impact Islamic and conventional stocks? Empirical evidence from QARDL technique," Resources Policy, Elsevier, vol. 66(C).
    57. Rehman, Mobeen Ur & Sensoy, Ahmet & Eraslan, Veysel & Shahzad, Syed Jawad Hussain & Vo, Xuan Vinh, 2021. "Sensitivity of US equity returns to economic policy uncertainty and investor sentiments," The North American Journal of Economics and Finance, Elsevier, vol. 57(C).
    58. Balcilar, Mehmet & Gupta, Rangan & Kim, Won Joong & Kyei, Clement, 2019. "The role of economic policy uncertainties in predicting stock returns and their volatility for Hong Kong, Malaysia and South Korea," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 150-163.
    59. Christina Christou & Juncal Cunado & Rangan Gupta & Christis Hassapis, 2016. "Economic Policy Uncertainty and Stock Market Returns in Pacific-Rim Countries: Evidence based on a Bayesian Panel VAR Model," Working Papers 201661, University of Pretoria, Department of Economics.
    60. Michele Costola & Michael Donadelli & Luca Gerotto & Ivan Gufler, 2022. "Global risks, the macroeconomy, and asset prices," Empirical Economics, Springer, vol. 63(5), pages 2357-2388, November.
    61. Nonejad, Nima, 2023. "Modeling the out-of-sample predictive relationship between equity premium, returns on the price of crude oil and economic policy uncertainty using multivariate time-varying dimension models," Energy Economics, Elsevier, vol. 126(C).
    62. Dang, Dandan & Fang, Hongsheng & He, Minyuan, 2019. "Economic policy uncertainty, tax quotas and corporate tax burden: Evidence from China," China Economic Review, Elsevier, vol. 56(C), pages 1-1.
    63. Han, Liyan & Liu, Yang & Yin, Libo, 2019. "Uncertainty and currency performance: A quantile-on-quantile approach," The North American Journal of Economics and Finance, Elsevier, vol. 48(C), pages 702-729.
    64. Phan, Dinh Hoang Bach & Sharma, Susan Sunila & Tran, Vuong Thao, 2018. "Can economic policy uncertainty predict stock returns? Global evidence," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 55(C), pages 134-150.
    65. Ruzhao Gao & Yancai Zhao & Bing Zhang, 2021. "The spillover effects of economic policy uncertainty on the oil, gold, and stock markets: Evidence from China," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 2134-2141, April.
    66. Pavitra Dhamija, 2020. "Economic Development and South Africa: 25 Years Analysis (1994 to 2019)," South African Journal of Economics, Economic Society of South Africa, vol. 88(3), pages 298-322, September.
    67. Sun, Xiaolei & Yao, Xiaoyang & Wang, Jun, 2017. "Dynamic interaction between economic policy uncertainty and financial stress: A multi-scale correlation framework," Finance Research Letters, Elsevier, vol. 21(C), pages 214-221.
    68. Batabyal, Sourav & Killins, Robert, 2021. "Economic policy uncertainty and stock market returns: Evidence from Canada," The Journal of Economic Asymmetries, Elsevier, vol. 24(C).
    69. Sinha, Avik & Mishra, Shekhar & Sharif, Arshian & Yarovaya, Larisa, 2021. "Does Green Financing help to improve the Environmental & Social Responsibility? Designing SDG framework through Advanced Quantile modelling," MPRA Paper 108150, University Library of Munich, Germany, revised 2021.
    70. Mehmet Balcilar & Deven Bathia & Riza Demirer & Rangan Gupta, 2017. "Credit Ratings and Predictability of Stock Returns and Volatility of the BRICS and the PIIGS: Evidence from a Nonparametric Causality-in-Quantiles Approach," Working Papers 201719, University of Pretoria, Department of Economics.
    71. Kais Tissaoui & Taha Zaghdoudi & Abdelaziz Hakimi & Ousama Ben-Salha & Lamia Ben Amor, 2022. "Does Uncertainty Forecast Crude Oil Volatility before and during the COVID-19 Outbreak? Fresh Evidence Using Machine Learning Models," Energies, MDPI, vol. 15(15), pages 1-20, August.

  8. Rangan Gupta & Anandamayee Majumdar, 2014. "Forecasting US Real House Price Returns over 1831-2013: Evidence from Copula Models," Working Papers 201444, University of Pretoria, Department of Economics.

    Cited by:

    1. Mawuli Segnon & Rangan Gupta & Keagile Lesame & Mark E. Wohar, 2019. "High-Frequency Volatility Forecasting of US Housing Markets," Working Papers 201977, University of Pretoria, Department of Economics.
    2. Alqaralleh, Huthaifa & Canepa, Alessandra & Salah Uddin, Gazi, 2023. "Dynamic relations between housing Markets, stock Markets, and uncertainty in global Cities: A Time-Frequency approach," The North American Journal of Economics and Finance, Elsevier, vol. 68(C).
    3. Kang, Sang Hoon & Uddin, Gazi Salah & Ahmed, Ali & Yoon, Seong-Min, 2018. "Multi-scale causality and extreme tail inter-dependence among housing prices," Economic Modelling, Elsevier, vol. 70(C), pages 301-309.
    4. Roman Matkovskyy, 2019. "Extremal Economic (Inter)Dependence Studies: A Case of the Eastern European Countries," Post-Print hal-02332090, HAL.
    5. Luis A. Gil-Alana & Rangan Gupta & Fernando Perez de Gracia, 2016. "Persistence, mean reversion and non-linearities in the US housing prices over 1830--2013," Applied Economics, Taylor & Francis Journals, vol. 48(34), pages 3244-3252, July.
    6. Sinha, Ankur & Kedas, Satishwar & Kumar, Rishu & Malo, Pekka, 2019. "Buy, Sell or Hold: Entity-Aware Classification of Business News," IIMA Working Papers WP 2019-04-02, Indian Institute of Management Ahmedabad, Research and Publication Department.
    7. Sun, Tianyu & Chand, Satish & Sharpe, Keiran, 2018. "Effect of Aging on Urban Land Prices in China," MPRA Paper 89237, University Library of Munich, Germany.
    8. Huthaifa Alqaralleh & Gazi Salah Uddin & Canepa, Alessandra, 2022. "Time-frequency connectedness across housing markets, stock market and uncertainty: A Wavelet-Time Varying Parameter Vector Autoregression," Department of Economics and Statistics Cognetti de Martiis. Working Papers 202204, University of Turin.

  9. Goodness C. Aye & Mehmet Balcilar Author-Name-First Mehmet & Rangan Gupta & Anandamayee Majumdar, 2014. "Forecasting Aggregate Retail Sales: The Case of South Africa," Working Papers 15-21, Eastern Mediterranean University, Department of Economics.

    Cited by:

    1. Uddin, Gazi Salah & Tang, Ou & Sahamkhadam, Maziar & Taghizadeh-Hesary, Farhad & Yahya, Muhammad & Cerin, Pontus & Rehme, Jakob, 2021. "Analysis of Forecasting Models in an Electricity Market under Volatility," ADBI Working Papers 1212, Asian Development Bank Institute.
    2. Wesley Marcos Almeida & Claudimar Pereira Veiga, 2023. "Does demand forecasting matter to retailing?," Journal of Marketing Analytics, Palgrave Macmillan, vol. 11(2), pages 219-232, June.
    3. Fildes, Robert & Ma, Shaohui & Kolassa, Stephan, 2022. "Retail forecasting: Research and practice," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1283-1318.
    4. Melchior, Cristiane & Zanini, Roselaine Ruviaro & Guerra, Renata Rojas & Rockenbach, Dinei A., 2021. "Forecasting Brazilian mortality rates due to occupational accidents using autoregressive moving average approaches," International Journal of Forecasting, Elsevier, vol. 37(2), pages 825-837.
    5. Erjiang E & Ming Yu & Xin Tian & Ye Tao, 2022. "Dynamic Model Selection Based on Demand Pattern Classification in Retail Sales Forecasting," Mathematics, MDPI, vol. 10(17), pages 1-16, September.
    6. Fildes, Robert & Ma, Shaohui & Kolassa, Stephan, 2019. "Retail forecasting: research and practice," MPRA Paper 89356, University Library of Munich, Germany.
    7. Ma, Shaohui & Fildes, Robert, 2020. "Forecasting third-party mobile payments with implications for customer flow prediction," International Journal of Forecasting, Elsevier, vol. 36(3), pages 739-760.
    8. Tran Tuan Anh, 2015. "Assessing the development potential of modern retail in Vietnam," HO CHI MINH CITY OPEN UNIVERSITY JOURNAL OF SCIENCE - ECONOMICS AND BUSINESS ADMINISTRATION, HO CHI MINH CITY OPEN UNIVERSITY JOURNAL OF SCIENCE, HO CHI MINH CITY OPEN UNIVERSITY, vol. 5(1), pages 31-40.
    9. Hoeltgebaum, Henrique & Borenstein, Denis & Fernandes, Cristiano & Veiga, Álvaro, 2021. "A score-driven model of short-term demand forecasting for retail distribution centers," Journal of Retailing, Elsevier, vol. 97(4), pages 715-725.
    10. Arunraj, Nari Sivanandam & Ahrens, Diane, 2015. "A hybrid seasonal autoregressive integrated moving average and quantile regression for daily food sales forecasting," International Journal of Production Economics, Elsevier, vol. 170(PA), pages 321-335.
    11. Emir Zunic & Kemal Korjenic & Kerim Hodzic & Dzenana Donko, 2020. "Application of Facebook's Prophet Algorithm for Successful Sales Forecasting Based on Real-world Data," Papers 2005.07575, arXiv.org.
    12. Chantal Rootman, 2016. "How social media tools influence brand image and buying behaviour in the South African food retail industry," Proceedings of Business and Management Conferences 3405542, International Institute of Social and Economic Sciences.
    13. Kourentzes, Nikolaos & Barrow, Devon & Petropoulos, Fotios, 2019. "Another look at forecast selection and combination: Evidence from forecast pooling," International Journal of Production Economics, Elsevier, vol. 209(C), pages 226-235.

  10. Rangan Gupta & Anandamayee Majumdar, 2011. "Reconsidering the Welfare Cost of Inflation in the US: A Nonparametric Estimation of the Nonlinear Long-Run Money Demand Equation using Projection Pursuit Regressions," Working Papers 201114, University of Pretoria, Department of Economics.

    Cited by:

    1. Wang, Qiang & Zhan, Lina, 2019. "Assessing the sustainability of the shale gas industry by combining DPSIRM model and RAGA-PP techniques: An empirical analysis of Sichuan and Chongqing, China," Energy, Elsevier, vol. 176(C), pages 353-364.
    2. Stephen M. Miller & Luis F. Martins & Rangan Gupta, 2014. "A Time-Varying Approach of the US Welfare Cost of Inflation," Working Papers 201419, University of Pretoria, Department of Economics.
    3. Matteo Mogliani & Giovanni Urga, 2018. "On the Instability of Long‐Run Money Demand and the Welfare Cost of Inflation in the United States," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 50(7), pages 1645-1660, October.
    4. Dong Liu & Chunlei Liu & Qiang Fu & Tianxiao Li & Muhammad Imran Khan & Song Cui & Muhammad Abrar Faiz, 2018. "Projection Pursuit Evaluation Model of Regional Surface Water Environment Based on Improved Chicken Swarm Optimization Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 32(4), pages 1325-1342, March.
    5. Plakandaras, Vasilios & Gupta, Rangan & Karmakar, Sayar & Wohar, Mark E., 2023. "Are real interest rates a monetary phenomenon? Evidence from 700 years of data," Research in International Business and Finance, Elsevier, vol. 66(C).
    6. Mohsen Bahmani-Oskooee & Majid Maki-Nayeri, 2018. "Asymmetric Effects of Policy Uncertainty on the Demand for Money in the United States," JRFM, MDPI, vol. 12(1), pages 1-13, December.
    7. Helmut Herwartz & Jordi Sardà & Bernd Theilen, 2016. "Money demand and the shadow economy: empirical evidence from OECD countries," Empirical Economics, Springer, vol. 50(4), pages 1627-1645, June.

  11. Mehmet Balcilar & Rangan Gupta & Anandamayee Majumdar & Stephen Miller, 2010. "Forecasting Nevada Gross Gaming Revenue and Taxable Sales Using Coincident and Leading Employment Indexes," Working Papers 15-01, Eastern Mediterranean University, Department of Economics.

    Cited by:

    1. Rangan Gupta, 2012. "Forecasting House Prices for the Four Census Regions and the Aggregate US Economy: The Role of a Data-Rich Environment," Working Papers 201214, University of Pretoria, Department of Economics.
    2. Mehmet Balcilar & Rangan Gupta & Anandamayee Majumdar & Stephen M. Miller, 2015. "Was the recent downturn in US real GDP predictable?," Applied Economics, Taylor & Francis Journals, vol. 47(28), pages 2985-3007, June.
    3. Mehmet Balcilar & Rangan Gupta & Anandamayee Majumdar & Stephen M. Miller, 2012. "Was the Recent Downturn in US GDP Predictable?," Working Papers 201230, University of Pretoria, Department of Economics.

Articles

  1. Bouri, Elie & Gupta, Rangan & Majumdar, Anandamayee & Subramaniam, Sowmya, 2021. "Time-varying risk aversion and forecastability of the US term structure of interest rates," Finance Research Letters, Elsevier, vol. 42(C).
    See citations under working paper version above.
  2. Rangan Gupta & Anandamayee Majumdar & Jacobus Nel & Sowmya Subramaniam, 2021. "Geopolitical Risks And The High-Frequency Movements Of The Us Term Structure Of Interest Rates," Annals of Financial Economics (AFE), World Scientific Publishing Co. Pte. Ltd., vol. 16(03), pages 1-16, September.
    See citations under working paper version above.
  3. Chang, Tsangyao & Gupta, Rangan & Majumdar, Anandamayee & Pierdzioch, Christian, 2019. "Predicting stock market movements with a time-varying consumption-aggregate wealth ratio," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 458-467.
    See citations under working paper version above.
  4. Balcilar, Mehmet & Gupta, Rangan & van Eyden, Reneé & Thompson, Kirsten & Majumdar, Anandamayee, 2018. "Comparing the forecasting ability of financial conditions indices: The case of South Africa," The Quarterly Review of Economics and Finance, Elsevier, vol. 69(C), pages 245-259.
    See citations under working paper version above.
  5. Rangan Gupta & Anandamayee Majumdar & Mark E. Wohar, 2017. "The Role of Current Account Balance in Forecasting the US Equity Premium: Evidence From a Quantile Predictive Regression Approach," Open Economies Review, Springer, vol. 28(1), pages 47-59, February.
    See citations under working paper version above.
  6. Gupta, Rangan & Majumdar, Anandamayee & Pierdzioch, Christian & Wohar, Mark E., 2017. "Do terror attacks predict gold returns? Evidence from a quantile-predictive-regression approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 65(C), pages 276-284.
    See citations under working paper version above.
  7. Bekiros, Stelios & Gupta, Rangan & Majumdar, Anandamayee, 2016. "Incorporating economic policy uncertainty in US equity premium models: A nonlinear predictability analysis," Finance Research Letters, Elsevier, vol. 18(C), pages 291-296.
    See citations under working paper version above.
  8. Rangan Gupta & Anandamayee Majumdar, 2015. "Forecasting US real house price returns over 1831-2013: evidence from copula models," Applied Economics, Taylor & Francis Journals, vol. 47(48), pages 5204-5213, October.
    See citations under working paper version above.
  9. Mehmet Balcilar & Rangan Gupta & Anandamayee Majumdar & Stephen M. Miller, 2015. "Was the recent downturn in US real GDP predictable?," Applied Economics, Taylor & Francis Journals, vol. 47(28), pages 2985-3007, June.

    Cited by:

    1. Gupta, Rangan & Wohar, Mark, 2017. "Forecasting oil and stock returns with a Qual VAR using over 150years off data," Energy Economics, Elsevier, vol. 62(C), pages 181-186.
    2. Juan Laborda & Sonia Ruano & Ignacio Zamanillo, 2023. "Multi-Country and Multi-Horizon GDP Forecasting Using Temporal Fusion Transformers," Mathematics, MDPI, vol. 11(12), pages 1-26, June.
    3. Jena, Pradyot Ranjan & Majhi, Ritanjali & Kalli, Rajesh & Managi, Shunsuke & Majhi, Babita, 2021. "Impact of COVID-19 on GDP of major economies: Application of the artificial neural network forecaster," Economic Analysis and Policy, Elsevier, vol. 69(C), pages 324-339.
    4. James D. Hamilton, 2017. "Why You Should Never Use the Hodrick-Prescott Filter," NBER Working Papers 23429, National Bureau of Economic Research, Inc.
    5. Lu, Xinjie & Ma, Feng & Wang, Tianyang & Wen, Fenghua, 2023. "International stock market volatility: A data-rich environment based on oil shocks," Journal of Economic Behavior & Organization, Elsevier, vol. 214(C), pages 184-215.

  10. Aye, Goodness C. & Balcilar, Mehmet & Gupta, Rangan & Majumdar, Anandamayee, 2015. "Forecasting aggregate retail sales: The case of South Africa," International Journal of Production Economics, Elsevier, vol. 160(C), pages 66-79.
    See citations under working paper version above.
  11. Rangan Gupta & Anandamayee Majumdar, 2014. "Reconsidering the welfare cost of inflation in the US: a nonparametric estimation of the nonlinear long-run money-demand equation using projection pursuit regressions," Empirical Economics, Springer, vol. 46(4), pages 1221-1240, June.
    See citations under working paper version above.
  12. Mehmet Balcilar & Rangan Gupta & Anandamayee Majumdar & Stephen Miller, 2013. "Forecasting Nevada gross gaming revenue and taxable sales using coincident and leading employment indexes," Empirical Economics, Springer, vol. 44(2), pages 387-417, April.
    See citations under working paper version above.
  13. Majumdar Anandamayee & Gries Corinna, 2010. "Bivariate Zero-Inflated Regression for Count Data: A Bayesian Approach with Application to Plant Counts," The International Journal of Biostatistics, De Gruyter, vol. 6(1), pages 1-26, August.

    Cited by:

    1. Brian Neelon & Dongjun Chung, 2017. "The LZIP: A Bayesian latent factor model for correlated zero-inflated counts," Biometrics, The International Biometric Society, vol. 73(1), pages 185-196, March.

  14. Majumdar, Anandamayee & Munneke, Henry J. & Gelfand, Alan E. & Banerjee, Sudipto & Sirmans, C.F., 2006. "Gradients in Spatial Response Surfaces With Application to Urban Land Values," Journal of Business & Economic Statistics, American Statistical Association, vol. 24, pages 77-90, January.

    Cited by:

    1. Fangpo Wang & Anirban Bhattacharya & Alan E. Gelfand, 2018. "Process modeling for slope and aspect with application to elevation data maps," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 27(4), pages 749-772, December.
    2. Abhimanyu Gupta & Javier Hidalgo, 2022. "Nonparametric prediction with spatial data," STICERD - Econometrics Paper Series 621, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
    3. Maria Terres & Alan Gelfand, 2015. "Using spatial gradient analysis to clarify species distributions with application to South African protea," Journal of Geographical Systems, Springer, vol. 17(3), pages 227-247, July.
    4. Fritsch, Markus & Haupt, Harry & Ng, Pin T., 2016. "Urban house price surfaces near a World Heritage Site: Modeling conditional price and spatial heterogeneity," Regional Science and Urban Economics, Elsevier, vol. 60(C), pages 260-275.
    5. Liangjun Su & Xi Qu, 2017. "Specification Test for Spatial Autoregressive Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 35(4), pages 572-584, October.
    6. Henry J. Munneke & C.F. Sirmans & Barrett A. Slade & Geoffrey K. Turnbull, 2014. "Housing Regulation, Externalities and Residential Property Prices," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 42(2), pages 422-456, June.
    7. Kuangyu Wen & Ximing Wu & David J. Leatham, 2021. "Spatially Smoothed Kernel Densities with Application to Crop Yield Distributions," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 26(3), pages 349-366, September.
    8. Harrison Quick & Sudipto Banerjee & Bradley P. Carlin, 2015. "Bayesian modeling and analysis for gradients in spatiotemporal processes," Biometrics, The International Biometric Society, vol. 71(3), pages 575-584, September.

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