Data for: Industry bubbles and unexpected consumption shocks: A cross-sectional explanation of stock returns under recursive preferences

We compile raw data from the Datastream database for all stocks traded on the Tokyo Stock Exchange. We use the filters suggested by Griffin et al. (2010) for Datastream series to exclude special purpose vehicles from data. Consequently, our sample comprises 3,866 stocks. We compile all macroeconomic series from the OECD Statistics section. Our dataset comprise the following series: 1 Japan_25_Portfolios_MV_PTBV_M: Monthly returns for 25 size-book-to-market equity portfolios, following the Fama and French (1993) methodology. 2 Japan_25_Portfolios_MV_DY_M: Monthly returns for 25 size-dividend yield portfolios, following the Fama and French (1993) methodology. 3 Japan_25_Portfolios_MV_PC_M: Monthly returns for 25 size-price-to-cash flow portfolios, following the Fama and French (1993) methodology. 4 Japan_3 Factors_M: Monthly returns for the portfolios that constitute the three classic Fama-French factors (RMRF, SMB and HML), following the Fama and French (1993) methodology. 5 Japan_5 Factors_M: Monthly returns for the portfolios that constitute the five Fama-French factors (RMRF, SMB, HML, RMW and CMA), following the Fama and French (2015) methodology. 6 Japan_RF_M: Three-month Treasury Bill rate for Japan. 7 Japan_C_Q: Private final consumption expenditure, in national currency and constant prices for Japan. 8 Japan_IK_Q: Investment-capital ratio, following the Cochrane (1991) methodology. We use gross capital formation series for Japan, in national currency, seasonally adjusted. We assume a depreciation rate of 0.1 and no adjustment cost. 9 Japan_DY_ConstrTech_M: Value-weighted dividend yield portfolios for Japanese firms in construction and technology industries, as proxied by two-digit SIC codes 15-17 and 36-48, respectively. 10 Japan_Bubbles_Q: Variation rates of construction and technology bubbles in Japan, as determined by a parameterized version of the bubble term in the Campbell and Shiller (1988) return identity, using the investment-capital ratio as an instrument. 11 Japan_Errors_Q: Residuals that result from the regression of consumption growth on the variation rate of construction and technology bubbles and the lagged consumption growth. REFERENCES: Campbell, J. Y., and Shiller, R. J. (1988). The Dividend-Price Ratio and Expectations of Future Dividends and Discount Factors, The Review of Financial Studies, 1, 195-228. Cochrane, J. H. (1991). Production-Based Asset Pricing and the Link Between Stock Returns and Economic Fluctuations, The Journal of Finance, 46, 209-237. Fama, E. F. and French, K. R. (1993). Common Risk Factors in the Returns on Stocks and Bonds, Journal of Financial Economics, 33, 3–56. Fama, E. F. and French, K. R. (2015). A Five-Factor Asset Pricing Model, Journal of Financial Economics, 116, 1-22. Griffin, J. M., Kelly, P., and Nardari, F. (2010). Do Market Efficiency Measures Yield Correct Inferences? A Comparison of Developed and Emerging Markets, Review of Financial Studies, 23, 3225–3277.本研究从Datastream数据库中获取东京证券交易所所有上市交易股票的原始数据，并采用格里芬等（Griffin et al., 2010）针对Datastream序列提出的筛选规则，剔除特殊目的载体样本。最终样本共包含3866只股票。所有宏观经济序列均取自经合组织（OECD）统计板块。 本数据集包含以下序列： 1. Japan_25_Portfolios_MV_PTBV_M：按照法玛与弗伦奇（Fama and French, 1993）方法构建的25个市值-账面市值比投资组合的月度收益率。 2. Japan_25_Portfolios_MV_DY_M：按照法玛与弗伦奇（Fama and French, 1993）方法构建的25个市值-股息率投资组合的月度收益率。 3. Japan_25_Portfolios_MV_PC_M：按照法玛与弗伦奇（Fama and French, 1993）方法构建的25个市值-现金流价格比投资组合的月度收益率。 4. Japan_3 Factors_M：按照法玛与弗伦奇（Fama and French, 1993）方法构建的经典三因子（RMRF、SMB与HML）对应投资组合的月度收益率。 5. Japan_5 Factors_M：按照法玛与弗伦奇（Fama and French, 2015）方法构建的五因子（RMRF、SMB、HML、RMW与CMA）对应投资组合的月度收益率。 6. Japan_RF_M：日本三个月国库券收益率。 7. Japan_C_Q：日本以本币计价的不变价私人最终消费支出。 8. Japan_IK_Q：按照科克伦（Cochrane, 1991）方法构建的投资-资本比序列。本研究采用日本经季节调整的本币计价总资本形成序列，并设定折旧率为0.1、无调整成本。 9. Japan_DY_ConstrTech_M：以市值加权的日本建筑与科技行业公司股息率投资组合，其中建筑行业和科技行业分别以二位标准行业分类码（Standard Industrial Classification, SIC）15-17与36-48作为划分依据。 10. Japan_Bubbles_Q：日本建筑与科技行业泡沫的变动率，该序列基于坎贝尔与席勒（Campbell and Shiller, 1988）收益率恒等式中的泡沫项参数化形式构建，并以投资-资本比作为工具变量。 11. Japan_Errors_Q：以消费增长率为被解释变量、建筑与科技行业泡沫变动率及滞后一期消费增长率为解释变量进行回归得到的残差序列。 参考文献： [1] 坎贝尔 J Y，席勒 R J. 股息价格比与未来股息和贴现因子预期[J]. 金融研究评论, 1988, 1: 195-228. [2] 科克伦 J H. 基于生产的资产定价与股票收益率和经济波动的关联[J]. 金融杂志, 1991, 46: 209-237. [3] 法玛 E F，弗伦奇 K R. 股票和债券收益率中的共同风险因子[J]. 金融经济学杂志, 1993, 33: 3-56. [4] 法玛 E F，弗伦奇 K R. 五因子资产定价模型[J]. 金融经济学杂志, 2015, 116: 1-22. [5] 格里芬 J M，凯利 P，纳尔达里 F. 市场效率度量能否得出正确推断？发达与新兴市场的比较[J]. 金融研究评论, 2010, 23: 3225-3277.