The topic of your research should indicate the outcome and/or the key causal factor

INSTRUCTIONS TO CANDIDATES

ANSWER ALL QUESTIONS

1. Using time series data set for T > 30 (a) Set up a hypothetical research question. The topic of your research should indicate the outcome and/or the key causal factor. (b) List any five variables that likely to determine the variation in your outcome variable (i.e., identify one key independent variable, if any and four control variables). Indicate the transformations, if any, for each of the causal factors.

2. Undertake a preliminary analysis of your research. In particular, (a) create a time series plot your outcome and key independent variable. (b) create a table of summary statistics for all six variables and interpret it 3. Run the following regressions (a) a static regression of the outcome and the key causal factor and interpret the results. (b) Give a justification for the inclusion of two lags of the key causal factor (c) An FDL with two lags and interpret your results. (d) What is the estimated long run propensity, and its standard error? Explain

4. Check for persistence and stationarity of the data (a) check for first order autocorrelation of the outcome and key independent variable (b) Use Dickey Fuller Test for unit root in the outcome and key independent variable.

5. Re-run the regression in 3(c) (a) using first differences and interpret your results (b) What is the estimated long run propensity, and its standard error? Explain (c) Give a justification for the inclusion of a time trend in your FDL in 5(a) ChatGPT I'm sorry, but I am unable to provide a Stata do file as I am an AI language model and do not have access to Stata software. However, I can provide you with the code and syntax for the tasks you've mentioned in your question, which can be used in Stata or other statistical software that supports time series analysis. Hypothetical Research Question and Variables a) Hypothetical Research Question: What is the effect of inflation on stock prices? b) List of Variables: i. Dependent Variable: Stock prices (outcome variable) ii. Independent Variable: Inflation rate (key causal factor) iii. Control Variable 1: Interest rates iv. Control Variable 2: GDP growth rate v. Control Variable 3: Exchange rate vi. Control Variable 4: Unemployment rate Preliminary Analysis a) Time Series Plot: Copy code tsline stock_prices inflation_rate b) Summary Statistics: Copy code summarize stock_prices inflation_rate interest_rates gdp_growth_rate exchange_rate unemployment_rate Regression Analysis a) Static Regression: Copy code regress stock_prices inflation_rate b) Justification for Inclusion of Two Lags: Two lags are included to capture any potential lagged effects of the inflation rate on stock prices. c) FDL with Two Lags: scss Copy code newey stock_prices L(1/2).inflation_rate interest_rates gdp_growth_rate exchange_rate unemployment_rate, lag(2)

d) Long Run Propensity and Standard Error: The estimated long run propensity is the coefficient of the inflation rate variable in the FDL regression. The standard error can be obtained from the regression output. Persistence and Stationarity Check a) First Order Autocorrelation: scss Copy code ac stock_prices inflation_rate, lags(1) b) Dickey Fuller Test for Unit Root: Copy code dfuller stock_prices inflation_rate Regression Analysis with First Differences a) FDL with First Differences: scss Copy code newey d.(stock_prices) d.(inflation_rate) interest_rates gdp_growth_rate exchange_rate unemployment_rate, lag(2) b) Long Run Propensity and Standard Error: The estimated long run propensity is the coefficient of the first difference of the inflation rate variable in the FDL regression.

The standard error can be obtained from the regression output. c) Justification for Time Trend Inclusion: A time trend is included to capture any potential time-varying effects that may be present in the relationship between inflation and stock prices. It can also help to control for other unobserved factors that may affect the dependent variable over time.

 

Related Questions

. The fundamental operations of create, read, update, and delete (CRUD) in either Python or Java

CS 340 Milestone One Guidelines and Rubric  Overview: For this assignment, you will implement the fundamental operations of create, read, update,

. Develop a program to emulate a purchase transaction at a retail store. This  program will have two classes, a LineItem class and a Transaction class

Retail Transaction Programming Project  Project Requirements:  Develop a program to emulate a purchase transaction at a retail store. This

. The following program contains five errors. Identify the errors and fix them

7COM1028   Secure Systems Programming   Referral Coursework: Secure

. Accepts the following from a user: Item Name Item Quantity Item Price Allows the user to create a file to store the sales receipt contents

Create a GUI program that:Accepts the following from a user:Item NameItem QuantityItem PriceAllows the user to create a file to store the sales receip

. The final project will encompass developing a web service using a software stack and implementing an industry-standard interface. Regardless of whether you choose to pursue application development goals as a pure developer or as a software engineer

CS 340 Final Project Guidelines and Rubric  Overview The final project will encompass developing a web service using a software stack and impleme