Econometrics Jobs

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Fixed-Price - Entry Level ($) - Est. Budget: $50 - Posted
I need help to match company identifiers across multiple financial databases. I have a database with 133,622 observations. In this database, I have CUSIP (8-digits), CUSIP (9-digists) and ISIN as company identifiers. For my research, I need to merge this database with three other databases, which are IBES for security analysts forecast information, COMPUSTAT for firm income and spending information, and CRSP for stock information. Because these three databases use different unique firm identifiers, please see the table below. I need to identify the corresponding GVKEY, PERMNO, and IBES ticker for the CUSIP in the primary database. The issue with CUSIP is that it changes over time for a company. So, for company A the CUSIP used in 2001 may be different to its CUSIP in 2003 or later. I will provide you with the primary database with four columns: CUSIP (8-digits), CUSIP (9-digists), ISIN, and a date. The output I’m looking for is the primary database with three additional columns, GVKEY, PERMNO, and IBES ticker. I can also provide you with one file that specify the match between CUSIP (9-digits) and GVKEY and PERMNO for different time period. Since GVKEY and PERMNO do not change over time, we can use this file to track the different CUSIP used for a firm across different years. In fact, there are already SAS code developed by WRDS to match IBES ticker and CRSP PERMNO. Since I always use STATA for my research and not familiar with SAS. I need help to process these. The SAS code to match IBES ticker to PERMNO The SAS code to add PERMNO to Compustat data Attached are two files: 1. A sample of the primary database with firm identifiers and date 2. A sample of the database showing the link between CUSIP, GVKEY, and PERMNO
Skills: Econometrics R SAS
Fixed-Price - Intermediate ($$) - Est. Budget: $30 - Posted
Am looking for a free lancer who could do the basic statistic work using stata software. I will be providing the data file which is quite easy to understand. Just to give an idea the questions I will be examining in order to verify the work are Compute the exact varaible ratio. Use the variables which i will provide. Describe the distribution of the variable and draw bar or pie chart. Obtain the descriptive statistics of a variable. Discuss your findings (e.g. how is the shape of the frequency distribution function? How the data set is spread around the mean? What is the best measure of central tendency and why? Stata working file and results in word file i would like to see. P.s during interviews or chat all queries will be cleared.
Skills: Econometrics Stata Statistics
Fixed-Price - Intermediate ($$) - Est. Budget: $30 - Posted
Consider the Classical Linear Regression Model (CLRM) Y = α +βX +ε where X denotes the independent GNI per capita, Atlas method (current US$), Y is the dependent variable Life expectancy at birth, total (years), α and β are unknown constants and ε is a random variable. Use a calculator and your sample to calculate ∑X, ∑Y, ∑XY and ∑X2. Use these values to write down the pair of ‘normal equations’ the solutions of which give the constant term (a) and the slope coefficient (b) of the fitted Ordinary Least Squares line Y = a + bX. i. Write down the equivalent matrix representation of the normal equations you have written in part. Explain how matrix algebra can be used to solve for the terms a and b. Data will be provided on request and further instructions in order to make the analysis smooth.
Skills: Econometrics Stata Statistics
Fixed-Price - Expert ($$$) - Est. Budget: $300 - Posted
I need to implement methodology using Bayesian analysis on a state space model. It uses KALMAN filter to estimate likelihood and uses Bayesian analysis to maximixe pposterior density. Please apply if you have experience in using KALMAN filter, Bayesian analysis for estimating posterior density in Python. More details to be shared later
Skills: Econometrics Python Python SciPy Statistics