├── .gitignore ├── K1996 ├── chapt26.xlsx └── README.md ├── README-sample.md ├── GM2016 ├── README.md └── replication_codes.ipynb └── README.md /.gitignore: -------------------------------------------------------------------------------- 1 | .DS_Store 2 | -------------------------------------------------------------------------------- /K1996/chapt26.xlsx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/d-jiao/open-source-replications/HEAD/K1996/chapt26.xlsx -------------------------------------------------------------------------------- /README-sample.md: -------------------------------------------------------------------------------- 1 | # \[Abbreviation of the paper\], \[Abbreviation of the journal\] 2 | Paper: \[Properly cite the paper\] 3 | 4 | Contributor: \[Include if you would like others to know who you are\] 5 | 6 | Email: \[Include if you would like others to reach out to you\] 7 | 8 | ## Introduction 9 | \[At the minimum, please list the tables you intend to replicate.\] 10 | 11 | ## Data Description 12 | I use the following data sources: 13 | - \[Name of the dataset\] (\[Url\]) 14 | 15 | I use the following steps to merge and clean the data... 16 | 17 | ## Technical Specification 18 | Coding Language: ... 19 | Software: ... 20 | 21 | ## Comments 22 | \[Anything you would like to discuss\] 23 | -------------------------------------------------------------------------------- /GM2016/README.md: -------------------------------------------------------------------------------- 1 | # GM2016, JFE 2 | Paper: Gormley, Todd A., and David A. Matsa. "Playing it safe? Managerial preferences, risk, and agency conflicts." Journal of Financial Economics 122.3 (2016): 431-455. 3 | 4 | Contributor: Dian Jiao 5 | 6 | Email: dj2526@columbia.edu 7 | 8 | ## Introduction 9 | I replicated Table 1, Table 2, and Table A.3 in the paper. 10 | 11 | ## Data Description 12 | I use the following data sources: 13 | 14 | - CRSP/Compustat Merged - Fundamentals Annual (https://wrds-www.wharton.upenn.edu/pages/get-data/center-research-security-prices-crsp/annual-update/crspcompustat-merged/fundamentals-annual/?saved_query=2861041) 15 | - CRSP/Compustat Merged - Fundamentals Quarterly (https://wrds-www.wharton.upenn.edu/pages/get-data/center-research-security-prices-crsp/quarterly-update/crspcompustat-merged/fundamentals-quarterly/?saved_query=2862850) 16 | - CRSP - Daily Stock File (https://wrds-www.wharton.upenn.edu/pages/get-data/center-research-security-prices-crsp/annual-update/stock-version-2/daily-stock-file/?saved_query=2861103) 17 | 18 | I use GVKEY to merge Fundamentals Annual with Fundamentals Quarterly. GVKEY is the primary identifier of Compustat, and using it can guarantee the best matching. To merge the fundamental data with CRSP, I use LPERMNO, and the merged dataset provided by WRDS facilitates the merge. To ensure that unexpected data needs to be entertained, I download the data from 1970 to 2009 and keep the sample from 1976 to 2006 after all the data processing clears. 19 | 20 | ## Technical Specification 21 | Coding Language: Python, Stata 22 | Software: jupyter notebook, Stata SE 23 | 24 | ## Comments 25 | There might be several reasons why the replication results are slightly different from those in the paper, including but not limited to 26 | - The authors used data on historical states of location and incorporation from Cohen (2012). This replication uses “STATE” and “INCORP” from Compustat. 27 | - The CRSP and Compustat datasets are constantly updating the data and the matching between the datasets to retrospectively correct possible errors. 28 | - The programming software and the version of the software might cause differences. 29 | - There might be nuanced differences in data collection and processing. 30 | -------------------------------------------------------------------------------- /K1996/README.md: -------------------------------------------------------------------------------- 1 | # K1996, JEL 2 | Paper: Kocherlakota, Narayana R. "The equity premium: It's still a puzzle." Journal of Economic Literature 34.1 (1996): 42-71. 3 | 4 | Contributor: Dian Jiao 5 | 6 | Email: dj2526@columbia.edu 7 | 8 | ## Introduction 9 | I replicated Figures 1 to 3 and Tables 1 to 4 in Kocherlakota (1996). As a validation check, I also replicate Grossman and Shiller 1981, p. 225, fig. 1. 10 | 11 | ## Data Description 12 | I use the consumption data from [Shiller’s website](http://www.econ.yale.edu/~shiller/data.htm). In my replication, I focuse on 1948 and onward. The red dotted line indicates the beginning of the sample period in my replication, and the black dotted line indicates the ending of the sample period in Kocherlakota (1996). 13 | 14 | Shiller's data does not include the 3-month treasury bill rate used in Kocherlakota (1996), so I used the real one-year interest rate as an approximation, which, though not identical, is arguably a reasonable proxy for the riskless rate. 15 | 16 | ## Technical Specification 17 | Coding Language: Python 18 | Software: jupyter notebook 19 | 20 | ## Comments 21 | There are two points I am unclear about the paper: 22 | 1. One puzzle is how Kocherlakota (1996) solves the case for $\alpha=1$ in Table 4, where the condition is not well-defined. 23 | 2. The second is the equation provided under Table 3, $e_t=\beta(c_{t+1}/c_t)^{-\alpha}(R_{t+1}^b-1)$ seems wrong. I followed equation (2b') instead, i.e., $e_t=\beta(c_{t+1}/c_t)^{-\alpha}R_{t+1}^b-1$. Only in this way was I able to replicate similar results. 24 | 25 | Some major differences: 26 | 1. In replicating Table 2, the sample means of $e$ vary more w.r.t. $\alpha$, and the t-stats are smaller. 27 | 2. In replicating Table 3, the t-stats are less significant. 28 | 3. In replicating Table 4, the fitted IESs vary less w.r.t. $\alpha$. 29 | 30 | My results differ from Kocherlakota's (1996) for two major reasons: 31 | - The distributional features of the variables are significantly different in the two sample periods (see the replicating figures). In particular, the stock return and real riskless rate are less volatile post-1948, and there are fewer negative real riskless rates appearing post-1948. 32 | - In my results, I use the real one-year interest rate as an approximation for the riskless rate, which is different from the nuanced data choices in Kocherlakota (1996). This causes observable differences even within the sample period of Kocherlakota (1996) (see the line charts). -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # open-source-replications 2 | This repository shares the open-sourced codes for replicating papers in the finance and accounting literature. I would like to invite you, my fellow researchers, to contribute to this project and make the research in our field more impactful. 3 | 4 | Please feel free to message me on GitHub or email me at dj2526@columbia.edu regarding any comments or suggestions. 5 | 6 | ## Who am I 7 | I am an accounting Ph.D. student at Columbia Business School, broadly interested in capital markets research and enthusiastic about applying the latest technology in my research. In my academic endeavors, I have always wished that I could find the replication codes for some well-established papers. That motivated me to initiate this project. Please feel free to read more about me [here](https://d-jiao.github.io/homepage/). 8 | 9 | ## How to Contribute 10 | I suggest the following steps 11 | 1. Create a folder named "**\[First letter of the authors, in alphabetical order\]\[Year of Publication\]\[Suffix in case of duplicated names\]**". For instance, "GM2016" would be the abbreviation for *Gormley, Todd A., and David A. Matsa. "Playing it safe? Managerial preferences, risk, and agency conflicts." Journal of Financial Economics 122.3 (2016): 431-455.* 12 | 2. Check whether the codes run as expected on a local machine and include them in the folder. 13 | 3. Include a README file in the folder detailing the name of the paper, the name and contact of you (optional), introduction, data description, technical specification, and comments (optional). See an example of the README file [here](https://github.com/d-jiao/open-source-replications/blob/main/GM2016/README.md) and a template [here](https://github.com/d-jiao/open-source-replications/blob/main/README-sample.md). 14 | 4. Include any other files you think are relevant in the folder, including but not limited to supporting data (if they are not huge) and intermediary outputs, etc. 15 | 6. Update the list of papers in THIS README file. 16 | 7. Commit and push to GitHub. See the wonderful technical document by GitHub [here](https://docs.github.com/en/get-started/quickstart/contributing-to-projects). 17 | 18 | ## Which papers have been replicated 19 | - **GM2016**: Gormley, Todd A., and David A. Matsa. "Playing it safe? Managerial preferences, risk, and agency conflicts." Journal of Financial Economics 122.3 (2016): 431-455. 20 | - **K1996**: Kocherlakota, Narayana R. "The equity premium: It's still a puzzle." Journal of Economic Literature 34.1 (1996): 42-71. 21 | 22 | ## Updates 23 | 11/17/2023: The project is initiated. -------------------------------------------------------------------------------- /GM2016/replication_codes.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": 1, 6 | "metadata": {}, 7 | "outputs": [ 8 | { 9 | "name": "stderr", 10 | "output_type": "stream", 11 | "text": [ 12 | ":219: RuntimeWarning: scipy._lib.messagestream.MessageStream size changed, may indicate binary incompatibility. Expected 56 from C header, got 64 from PyObject\n" 13 | ] 14 | }, 15 | { 16 | "name": "stdout", 17 | "output_type": "stream", 18 | "text": [ 19 | "\n", 20 | " ___ ____ ____ ____ ____ ®\n", 21 | " /__ / ____/ / ____/ 17.0\n", 22 | "___/ / /___/ / /___/ SE—Standard Edition\n", 23 | "\n", 24 | " Statistics and Data Science Copyright 1985-2021 StataCorp LLC\n", 25 | " StataCorp\n", 26 | " 4905 Lakeway Drive\n", 27 | " College Station, Texas 77845 USA\n", 28 | " 800-STATA-PC https://www.stata.com\n", 29 | " 979-696-4600 stata@stata.com\n", 30 | "\n", 31 | "Stata license: Single-user , expiring 17 Feb 2024\n", 32 | "Serial number: 401709210983\n", 33 | " Licensed to: Dian\n", 34 | " Columbia Business School\n", 35 | "\n", 36 | "Notes:\n", 37 | " 1. Unicode is supported; see help unicode_advice.\n", 38 | " 2. Maximum number of variables is set to 5,000; see help set_maxvar.\n" 39 | ] 40 | } 41 | ], 42 | "source": [ 43 | "import pandas as pd\n", 44 | "import numpy as np\n", 45 | "from linearmodels import PanelOLS\n", 46 | "import warnings\n", 47 | "# the feature of STATA 17 SE is used to run the stata codes in the jupyter notebook\n", 48 | "# this is because the python package cannot handle three-way fixed effects and reghdfe is needed \n", 49 | "# the stata codes can also be run in the stata program \n", 50 | "import stata_setup\n", 51 | "\n", 52 | "stata_setup.config(\"C:\\Program Files\\Stata17\", \"se\")\n", 53 | "warnings.filterwarnings('ignore')" 54 | ] 55 | }, 56 | { 57 | "cell_type": "code", 58 | "execution_count": 4, 59 | "metadata": {}, 60 | "outputs": [], 61 | "source": [ 62 | "# CRSP/Compustat Merged - Fundamentals Annual\n", 63 | "# https://wrds-www.wharton.upenn.edu/pages/get-data/center-research-security-prices-crsp/annual-update/crspcompustat-merged/fundamentals-annual/?saved_query=2861041\n", 64 | "funda = pd.read_csv('funda2.csv.gz') \n", 65 | "# CRSP/Compustat Merged - Fundamentals Quarterly\n", 66 | "# https://wrds-www.wharton.upenn.edu/pages/get-data/center-research-security-prices-crsp/quarterly-update/crspcompustat-merged/fundamentals-quarterly/?saved_query=2862850\n", 67 | "fundq = pd.read_csv('fundq.csv.gz')\n", 68 | "# CRSP - Daily Stock File\n", 69 | "# https://wrds-www.wharton.upenn.edu/pages/get-data/center-research-security-prices-crsp/annual-update/stock-version-2/daily-stock-file/?saved_query=2861103\n", 70 | "crsp = pd.read_csv('crsp.csv.zip')" 71 | ] 72 | }, 73 | { 74 | "cell_type": "code", 75 | "execution_count": 5, 76 | "metadata": {}, 77 | "outputs": [], 78 | "source": [ 79 | "'''\n", 80 | "preliminary cleaning \n", 81 | "crsp: add a column for squared daily return\n", 82 | "fundq: calculate quarterly cash-flow-to-asset ratio\n", 83 | "funda: filter out the companies excluded in the paper (we use funda to build and merge the full datasets, so we don't need to repeat the filtering for \n", 84 | "crsp and fundq)\n", 85 | "'''\n", 86 | "\n", 87 | "crsp['cyear'] = crsp['DlyCalDt'].apply(lambda x: x[:4]).astype(int)\n", 88 | "# the paper requires that the standard deviation be calculated using annualized average sum of squares\n", 89 | "crsp['ret2'] = crsp['DlyRet']**2\n", 90 | "\n", 91 | "# create the indexing for year-quarter\n", 92 | "fundq['yearq'] = fundq['fyearq'] + (fundq['fqtr'] - 1) / 4\n", 93 | "fundq = fundq.sort_values(['gvkey', 'yearq']).reset_index(drop=True)\n", 94 | "fundq['accruals'] = fundq.groupby(['gvkey'])['actq'].diff() - fundq.groupby(['gvkey'])['cheq'].diff() - fundq.groupby(['gvkey'])['lctq'].diff() \\\n", 95 | " + fundq.groupby(['gvkey'])['dlcq'].diff() - fundq['dpq']\n", 96 | "# remove the observations with missing last-quarter data (i.e., the difference in year-quarter indexing is not 0.25)\n", 97 | "fundq.loc[fundq.groupby(['gvkey'])['yearq'].diff() != .25, 'accruals'] = np.nan\n", 98 | "# quarterly cash-flow-to-asset ratio\n", 99 | "fundq['cf2a'] = (fundq['oiadpq'] - fundq['accruals']) / fundq.groupby(['gvkey'])['atq'].shift(1)\n", 100 | "fundq = fundq.rename(columns={'gvkey': 'GVKEY'})\n", 101 | "\n", 102 | "# remove egulated utility firms (SIC codes 4900–4999)\n", 103 | "funda = funda[~((funda['sic']>=4900)&(funda['sic']<=4999))]\n", 104 | "# remove firms located or incorporated outside the US (built on sample STATA codes)\n", 105 | "state_list = 'keep if incorp == \"AK\" | incorp == \"AL\" | incorp == \"AR\" | incorp == \"AZ\" | incorp == \"CA\" | incorp == \"CO\" | incorp == \"CT\" | incorp == \"DC\" | incorp == \"DE\" | incorp == \"FL\" | incorp == \"GA\" | incorp == \"HI\" | incorp == \"ID\" | incorp == \"IL\" | incorp == \"IN\" | incorp == \"IA\" | incorp == \"KS\" | incorp == \"KY\" | incorp == \"LA\" | incorp == \"ME\" | incorp == \"MD\" | incorp == \"MA\" | incorp == \"MI\" | incorp == \"MN\" | incorp == \"MS\" | incorp == \"MO\" | incorp == \"MT\" | incorp == \"NE\" | incorp == \"NV\" | incorp == \"NH\" | incorp == \"NJ\" | incorp == \"NM\" | incorp == \"NY\" | incorp == \"NC\" | incorp == \"ND\" | incorp == \"OH\" | incorp == \"OK\" | incorp == \"OR\" | incorp == \"PA\" | incorp == \"RI\" | incorp == \"SC\" | incorp == \"SD\" | incorp == \"TN\" | incorp == \"TX\" | incorp == \"UT\" | incorp == \"VT\" | incorp == \"VA\" | incorp == \"WA\" | incorp == \"WV\" | incorp == \"WI\" | incorp == \"WY\"'\n", 106 | "state_list = state_list.split('\"')[1::2]\n", 107 | "funda = funda[funda['state'].isin(state_list)]\n", 108 | "funda = funda[funda['incorp'].isin(state_list)]\n", 109 | "# remove firm-year observations with either missing or negative assets or sales\n", 110 | "funda = funda[funda['sale'] > 0]\n", 111 | "funda = funda[funda['at'] > 0] " 112 | ] 113 | }, 114 | { 115 | "cell_type": "code", 116 | "execution_count": 6, 117 | "metadata": {}, 118 | "outputs": [], 119 | "source": [ 120 | "'''\n", 121 | "merge the datasets from CRSP and Fundamentals Quarterly to the dataset from Fundamentals Annual\n", 122 | "what we need from CRSP: annualized vol of stock return \n", 123 | "what we need from Fundamentals Quarterly: annual vol of cash-flow-to-asset ratio\n", 124 | "'''\n", 125 | "\n", 126 | "df1 = crsp.groupby(['cyear', 'PERMNO'])['ret2'].mean().reset_index()\n", 127 | "df1.columns = ['fyear', 'LPERMNO', 'ret_vol']\n", 128 | "df1['ret_vol'] = np.sqrt(df1['ret_vol'] * 252)\n", 129 | "\n", 130 | "df2 = fundq.groupby(['GVKEY', 'fyearq'])['cf2a'].std().reset_index()\n", 131 | "df2.columns = ['GVKEY', 'fyear', 'cf_vol']\n", 132 | "\n", 133 | "# use gvkey, the primary identifier of Compustat, to merge funda and fundq to ensure best match\n", 134 | "df = pd.merge(funda, df2, how='left')\n", 135 | "# use LPERMNO to merge funda and crsp, as provided by the CRSP/Compustat Merged Database\n", 136 | "df = pd.merge(df, df1, how='left')\n", 137 | "df = df.sort_values(['GVKEY', 'fyear']).reset_index(drop=True)" 138 | ] 139 | }, 140 | { 141 | "cell_type": "code", 142 | "execution_count": 7, 143 | "metadata": {}, 144 | "outputs": [], 145 | "source": [ 146 | "'''\n", 147 | "Main variables of interest\n", 148 | "'''\n", 149 | "\n", 150 | "# ln(assets): Calculated from Compustat using ln(at)\n", 151 | "df['ln_assets'] = np.log(df['at'])\n", 152 | "\n", 153 | "# ROA: Calculated from Compustat using ni / at\n", 154 | "df['roa'] = df['ni'] / df['at']\n", 155 | "\n", 156 | "# debt/assets: Calculated from Compustat using (dltt + dlc) / at\n", 157 | "df['leverage'] = (df['dltt'] + df['dlc']) / df['at']\n", 158 | "\n", 159 | "# three-year asset CAGR: Calculated from Compustat using [$(at_t / at_{t-3})^{1/3}$ − 1] × 100; CAGR = compounded annual growth rate.\n", 160 | "df['asset_cagr'] = ((df['at'] / df.groupby(['LPERMNO'])['at'].shift(3)) ** (1/3) - 1) * 100\n", 161 | "# replace the 3-year growth rate where year t-3 is missing with NaN\n", 162 | "df.loc[df['fyear'] - df.groupby(['LPERMNO'])['fyear'].shift(3) != 3, 'asset_cagr'] = np.nan\n", 163 | "\n", 164 | "# ln(cash): Calculated from Compustat using ln(ch).\n", 165 | "df['ln_cash'] = np.log(df['ch'])\n", 166 | "\n", 167 | "# stock volatitily: ret_vol from df1\n", 168 | "# Calculated from CRSP using the square root of the sum of squared daily returns over the year. \n", 169 | "# To adjust for differences in the number of trading days, the raw sum is multiplied by 252 and divided by the number of trading days\n", 170 | "\n", 171 | "# Cash flow/Assets: Calculated from Compustat using $(oiadp_t - accruals_t) / at_{t−1}$, where $accruals_t = (act_t − act_{t−1}) − (che_t − che_{t−1}) − (lct_t − lct_{t−1}) + (dlc_t − dlc_{t−1}) − dp_t$.\n", 172 | "# df['cf_vol'] merged from df2\n", 173 | "\n", 174 | "# operating asset volatity: Stock volatility × [E / (V − C)], where E / (V − C) is calculated from Compustat using (csho × prcc_f) / [lt + (csho × prcc_f) − ch]\n", 175 | "df['oav'] = df['csho'] * df['prcc_f'] / (df['lt'] + df['csho'] * df['prcc_f'] - df['ch']) * df['ret_vol']\n", 176 | "\n", 177 | "# replace infinities with NaN (this might arise from division by 0, logarithm of 0, etc.)\n", 178 | "df = df.replace([np.inf, -np.inf], np.nan)" 179 | ] 180 | }, 181 | { 182 | "cell_type": "code", 183 | "execution_count": 8, 184 | "metadata": {}, 185 | "outputs": [], 186 | "source": [ 187 | "'''\n", 188 | "create the main variable: BC Law\n", 189 | "the computation is based on Table A1 of the paper\n", 190 | "'''\n", 191 | "\n", 192 | "bc_state = ['AZ', 'CT', 'DE', 'GA', 'ID', 'IL', 'IN', 'IA', 'KS', 'KY', 'ME', 'MD', 'MA', 'MI', 'MN', 'MO', 'NE', 'NV', \n", 193 | "'NJ', 'NY', 'OK', 'OH', 'OR', 'PA', 'RI', 'SC', 'SD', 'TN', 'TX', 'VA', 'WA', 'WI', 'WY']\n", 194 | "bc_year = [1987, 1989, 1988, 1988, 1988, 1989, 1986, 1997, 1989, 1987, 1988, 1989, 1989, 1989, 1987, 1986, 1988, 1991, \n", 195 | "1986, 1985, 1991, 1990, 1991, 1989, 1990, 1988, 1990, 1988, 1997, 1988, 1987, 1987, 1989]\n", 196 | "\n", 197 | "bc_dict = dict(zip(bc_state, bc_year))\n", 198 | "\n", 199 | "df['bc_year'] = df['incorp'].apply(lambda x: bc_dict[x] if x in bc_dict.keys() else 2100)\n", 200 | "df['bc_law'] = (df['fyear'] >= df['bc_year']).astype(int)" 201 | ] 202 | }, 203 | { 204 | "cell_type": "code", 205 | "execution_count": 9, 206 | "metadata": {}, 207 | "outputs": [], 208 | "source": [ 209 | "'''\n", 210 | "produce the final dataset\n", 211 | "'''\n", 212 | "# take the sample period (data from 1970 to 2009 in the original dataset is downloaded in case of other needs)\n", 213 | "df = df[(df['fyear']>=1976)&(df['fyear']<=2006)]\n", 214 | "\n", 215 | "# winsorize the numerical features on 1% level (into 99% interval)\n", 216 | "numerical = ['ln_assets', 'roa', 'leverage', 'asset_cagr', 'ret_vol', 'cf_vol', 'ln_cash', 'oav']\n", 217 | "df[numerical] = df[numerical].clip(lower=df[ numerical].quantile(0.005), upper=df[numerical].quantile(0.995), axis=1).values\n", 218 | "df.to_stata('reg.dta')" 219 | ] 220 | }, 221 | { 222 | "cell_type": "code", 223 | "execution_count": 10, 224 | "metadata": {}, 225 | "outputs": [], 226 | "source": [ 227 | "'''\n", 228 | "replication of table 1, columns 1 and 2 (this is not required, provided to check the data consistency)\n", 229 | "'''\n", 230 | "\n", 231 | "col1 = df[(df['bc_year']==df['fyear']+1)|(df['bc_year']==df['fyear']+2)|(df['bc_year']==df['fyear']+3)]\n", 232 | "col2 = df[df['fyear'].isin(col1['fyear'].values)&(df['bc_year']!=df['fyear']+1)&(df['bc_year']!=df['fyear']+2)&(df['bc_year']!=df['fyear']+3)]\n", 233 | "\n", 234 | "table1 = pd.DataFrame(columns=['', 'BC law', 'No BC law'])\n", 235 | "\n", 236 | "for var in ['ln_assets', 'roa', 'leverage', 'asset_cagr', 'ret_vol', 'cf_vol']:\n", 237 | " table1 = table1.append(pd.Series([var, \n", 238 | " '%.3f' % col1[var].mean(), \n", 239 | " '%.3f' % col2[var].mean()], index=table1.columns), ignore_index=True)\n", 240 | " table1 = table1.append(pd.Series(['', '(%.3f)' % col1[var].std(), '(%.3f)' % col2[var].std()], index=table1.columns), ignore_index=True)\n", 241 | "\n", 242 | "table1 = table1.append(pd.Series(['N', len(col1), len(col2)], index=table1.columns), ignore_index=True)\n", 243 | "table1.to_csv('table1.csv', index=False)" 244 | ] 245 | }, 246 | { 247 | "attachments": { 248 | "image.png": { 249 | "image/png": "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" 250 | } 251 | }, 252 | "cell_type": "markdown", 253 | "metadata": {}, 254 | "source": [ 255 | "![image.png](attachment:image.png)" 256 | ] 257 | }, 258 | { 259 | "cell_type": "code", 260 | "execution_count": 11, 261 | "metadata": {}, 262 | "outputs": [], 263 | "source": [ 264 | "'''\n", 265 | "replication of table A3, rows 1, 3, 4 and 5 (this is not required, provided to check the data consistency)\n", 266 | "'''\n", 267 | "\n", 268 | "tablea3 = df[['ret_vol', 'oav', 'cf_vol', 'ln_cash']].agg([np.mean, np.median, np.std]).T\n", 269 | "tablea3.round(3)\n", 270 | "tablea3.to_csv('tablea3.csv')" 271 | ] 272 | }, 273 | { 274 | "attachments": { 275 | "image.png": { 276 | "image/png": "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" 277 | } 278 | }, 279 | "cell_type": "markdown", 280 | "metadata": {}, 281 | "source": [ 282 | "![image.png](attachment:image.png)" 283 | ] 284 | }, 285 | { 286 | "cell_type": "code", 287 | "execution_count": 15, 288 | "metadata": {}, 289 | "outputs": [ 290 | { 291 | "name": "stdout", 292 | "output_type": "stream", 293 | "text": [ 294 | "\n", 295 | ". * replication of table 2, columns 1, 3, 4 and 5\n", 296 | ". \n", 297 | ". set matsize 2000, permanently\n", 298 | "(set matsize preference recorded)\n", 299 | "set matsize ignored.\n", 300 | " Matrix sizes are no longer limited by c(matsize) in modern Statas.\n", 301 | " Matrix sizes are now limited by edition of Stata. See limits for more\n", 302 | " details.\n", 303 | "\n", 304 | ". use reg.dta, clear\n", 305 | "\n", 306 | ". \n", 307 | ". egen state_year = group(fyear state)\n", 308 | "\n", 309 | ". egen industry_year = group(fyear sic)\n", 310 | "\n", 311 | ". \n", 312 | ". quietly reghdfe ret_vol bc_law, absorb(GVKEY state_year industry_year) cluste\n", 313 | "> r(incorp) noconstant\n", 314 | "\n", 315 | ". outreg2 using table2.xls, se tdec(2) bdec(3) addstat(Adj. R-squared, e(r2_a))\n", 316 | "> addtext(Firm-Fixed Effects, Yes, State-Year-Fixed Effects, Yes, Industry-Year\n", 317 | "> -Fixed Effects, Yes, Cluster, State-of-Incorp) replace\n", 318 | "table2.xls\n", 319 | "dir : seeout\n", 320 | "\n", 321 | ". \n", 322 | ". quietly reghdfe oav bc_law, absorb(GVKEY state_year industry_year) cluster(in\n", 323 | "> corp) noconstant\n", 324 | "\n", 325 | ". outreg2 using table2.xls, se tdec(2) bdec(3) addstat(Adj. R-squared, e(r2_a))\n", 326 | "> addtext(Firm-Fixed Effects, Yes, State-Year-Fixed Effects, Yes, Industry-Year\n", 327 | "> -Fixed Effects, Yes, Cluster, State-of-Incorp) append\n", 328 | "table2.xls\n", 329 | "dir : seeout\n", 330 | "\n", 331 | ". \n", 332 | ". quietly reghdfe cf_vol bc_law, absorb(GVKEY state_year industry_year) cluster\n", 333 | "> (incorp) noconstant\n", 334 | "\n", 335 | ". outreg2 using table2.xls, se tdec(2) bdec(3) addstat(Adj. R-squared, e(r2_a))\n", 336 | "> addtext(Firm-Fixed Effects, Yes, State-Year-Fixed Effects, Yes, Industry-Year\n", 337 | "> -Fixed Effects, Yes, Cluster, State-of-Incorp) append\n", 338 | "table2.xls\n", 339 | "dir : seeout\n", 340 | "\n", 341 | ". \n", 342 | ". quietly reghdfe ln_cash bc_law, absorb(GVKEY state_year industry_year) cluste\n", 343 | "> r(incorp) noconstant\n", 344 | "\n", 345 | ". outreg2 using table2.xls, se tdec(2) bdec(3) addstat(Adj. R-squared, e(r2_a))\n", 346 | "> addtext(Firm-Fixed Effects, Yes, State-Year-Fixed Effects, Yes, Industry-Year\n", 347 | "> -Fixed Effects, Yes, Cluster, State-of-Incorp) append\n", 348 | "table2.xls\n", 349 | "dir : seeout\n", 350 | "\n", 351 | ". \n" 352 | ] 353 | } 354 | ], 355 | "source": [ 356 | "%%stata\n", 357 | "* replication of table 2, columns 1, 3, 4 and 5\n", 358 | "\n", 359 | "set matsize 2000, permanently\n", 360 | "use reg.dta, clear\n", 361 | "\n", 362 | "egen state_year = group(fyear state)\n", 363 | "egen industry_year = group(fyear sic)\n", 364 | "\n", 365 | "quietly reghdfe ret_vol bc_law, absorb(GVKEY state_year industry_year) cluster(incorp) noconstant\n", 366 | "outreg2 using table2.xls, se tdec(2) bdec(3) addstat(Adj. R-squared, e(r2_a))addtext(Firm-Fixed Effects, Yes, State-Year-Fixed Effects, Yes, Industry-Year-Fixed Effects, Yes, Cluster, State-of-Incorp) replace\n", 367 | "\n", 368 | "quietly reghdfe oav bc_law, absorb(GVKEY state_year industry_year) cluster(incorp) noconstant\n", 369 | "outreg2 using table2.xls, se tdec(2) bdec(3) addstat(Adj. R-squared, e(r2_a))addtext(Firm-Fixed Effects, Yes, State-Year-Fixed Effects, Yes, Industry-Year-Fixed Effects, Yes, Cluster, State-of-Incorp) append\n", 370 | " \n", 371 | "quietly reghdfe cf_vol bc_law, absorb(GVKEY state_year industry_year) cluster(incorp) noconstant\n", 372 | "outreg2 using table2.xls, se tdec(2) bdec(3) addstat(Adj. R-squared, e(r2_a))addtext(Firm-Fixed Effects, Yes, State-Year-Fixed Effects, Yes, Industry-Year-Fixed Effects, Yes, Cluster, State-of-Incorp) append\n", 373 | "\n", 374 | "quietly reghdfe ln_cash bc_law, absorb(GVKEY state_year industry_year) cluster(incorp) noconstant\n", 375 | "outreg2 using table2.xls, se tdec(2) bdec(3) addstat(Adj. R-squared, e(r2_a))addtext(Firm-Fixed Effects, Yes, State-Year-Fixed Effects, Yes, Industry-Year-Fixed Effects, Yes, Cluster, State-of-Incorp) append" 376 | ] 377 | }, 378 | { 379 | "attachments": { 380 | "image.png": { 381 | "image/png": "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" 382 | } 383 | }, 384 | "cell_type": "markdown", 385 | "metadata": {}, 386 | "source": [ 387 | "![image.png](attachment:image.png)" 388 | ] 389 | } 390 | ], 391 | "metadata": { 392 | "kernelspec": { 393 | "display_name": "Python 3", 394 | "language": "python", 395 | "name": "python3" 396 | }, 397 | "language_info": { 398 | "codemirror_mode": { 399 | "name": "ipython", 400 | "version": 3 401 | }, 402 | "file_extension": ".py", 403 | "mimetype": "text/x-python", 404 | "name": "python", 405 | "nbconvert_exporter": "python", 406 | "pygments_lexer": "ipython3", 407 | "version": "3.8.8" 408 | } 409 | }, 410 | "nbformat": 4, 411 | "nbformat_minor": 4 412 | } 413 | --------------------------------------------------------------------------------