Factors Affecting the Social Culture | Online Assignment Help

A team of sociologists are interested in finding out what factors affect the social culture within a workplace. In particular they want to understand the variables that influence the number of internal complaints and harassment claims that a firm experiences. They wish to know whether increasing profitability does anything to lower the incidence of these claims.  The sociologists are aware that the statistical association between claims and profitability may reflect (i) the causal effect of profitability on harassment, and (ii) the effect of harassment on profitability, and that this complicates their analysis.

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The file workplace.dta has data on the average number of claims, the size of a firm, the gender ratio (males to females), the average age, and the firm’s profitability. There are also two variables that are related to the profitability of the firm but have nothing to do with its internal culture. These are the industry growth rate (ig) and the local economic growth rate (ec) that the firm experiences.

  1. Estimate an equation governing the number of claims for a firm based only on the firm level data. What is the effect of profitability in this model?


  1. You suspect that harassment claims and profitability may be endogenous. Briefly explain why this may be so, and why it would bias the parameter estimate in part 1.


  1. To correct for endogeneity you decide to use a 2SLS procedure.  Using ig and ec as instruments, give the estimated reduced from (first stage) regression. Is the model well identified?


  1. Using the built in 2SLS procedure in Eviews, estimate the effect of profitability on harassment claims while correcting for endogeneity. Does poor firm performance damage its internal culture? How does the estimate produced here compare to the one given in part 1?


  1. Briefly explain why ig and ec are suitable instruments for correcting endogeneity bias in this problem.


Q2: 6 marks

Development economists are often interested in the determinants of production in impoverished parts of the world. An area of particular focus in recent years has been agricultural output.  When farming is successful, there are large positive spill-over effects for local economies. Conversely when crops fail or livestock die, famine and associated problems such as the spread of disease often follow. Consequently, by identifying policies that lead to increased agricultural yields, economic research can contribute to substantial welfare gains.

Your task is to assess the effectiveness of an agricultural assistance program implemented in Tanzania.  The assistance program involved visits to small family farms where farmers were provided with some training and were given access to fertilizer. Data were taken on farms that did and did not participate in the program, and information was collected twice – shortly before the program was implemented, and one year afterwards.

The data are available in the workfile Agriculture.wf1. Dummy variables program and after identify farms that participated, and the time period after the program was implemented. Agricultural output is measured in US dollars per person-hectare, and is stored in the variable yield. You also have information on the age of the farmer (age), the size of the farm (size), an index summarizing labour input (labour), rainfall in the last 12 months (rainfall), and an indicator of whether or not the farmer has completed seven years of schooling (school).


  1. To assess the effectiveness of the program a difference-in-differences estimator can be used. Briefly explain the concept of a “parallel trend” for this estimator and what this assumption implies for the agricultural assistance program.


  1. Why can’t we estimate the effectiveness of the program by simply averaging the output rates of farms that did and did not participate in the program? Briefly explain.


  1. Calculate the difference-in-difference estimate of the effectiveness of the program (in terms of output) based only upon average rates before and after implementation.


  1. Give the regression equation that would be used to calculate the full difference-in-difference estimate employing the full set of control variables. Also estimate this equation and interpret the results. Why is this estimate preferable to the estimate given in part 3?


  1. Briefly perform some diagnostics on your model.  Do the coefficients make sense? Are there any signs of misspecification? Are the residuals in line with your assumptions?


Q3 4 marks

GDP growth in Australia is thought to be affected over time by economic growth in China and Japan.  Data from 1970 to 2009 can be found in growth.wf1 where AUS denotes the annual change in Australian GDP growth rates, CHN denotes the same for Chinese economic growth and JAP for Japanese economic growth. All variables are stationary.

You are to investigate time-series determinants of economic growth by estimating a model for Australian output based on the current and lagged performances of the three countries.

  1. Determine a specific model ARDL(P,Q) model with appropriate lag lengths (i.e. values for P and Q) explaining foreign determinants of Australian growth. Ensure that the residuals do not suffer from autocorrelation. Investigate this with (i) a correlogram giving Q-statistics and (ii) a Lagrange Multiplier test. Report the estimated equation of your chosen model, and explain why you have settled on this specification.


  1. Write a paragraph or two on the estimated dynamic relationship between the Australian and Chinese/Japanese economic performances based upon the output from part 1.  Refer particularly to the magnitudes, significance and interpretations of the coefficients.

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