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Regression analysis

Your CEO wants to better understand the factors driving employee turnover, and she has asked you to take the lead in conducting the analyses.

You should begin with data cleaning and range checks. Expect that there are problems here, as with most any large dataset! Please address any problems that you find and document any changes that you have made in your memo to me.

Then, move on to the basics (e.g., are departing employees older, younger, have higher education levels, lower job satisfaction, etc.)? You should also seek to determine whether or not there are any differences in attrition across departments and if so, why.

Once you have outlined the basics, develop a multivariate regression model to determine which factors appear to be the most important predictors of Probability of Turnover and/or Turnover (be sure to use a logistic regression model if you focus on the latter). Note that you have a lot of discretion in how you approach this problem, so I am intentionally not providing step-by-step details on what you should do with these projects. I want you to show me how you would approach the problem.

Sample Solution

loyment, without work – was forecasted to be 44.337% during the December period of 2019. An almost 10% increase since the year prior illustrating the apparent negative impact inflation has on employment (CEIC 2019). In the short term, individuals are likely to supply labour despite the acceleration in inflation due to the higher wages. According to the Phillips curve, inflation and unemployment maintain an inverse relationship meaning low levels of unemployment correspond to higher levels of inflation and high unemployment corresponds to lower levels of inflation – potentially deflation. Logically, this makes sense as high unemployment would put a downward pressure on prices of goods and reduce inflation. This is because a lack of income makes excess expenditure less permissive. However, in the case of Venezuela, it differs. Venezuela is undergoing extremely high inflation as well as relatively high unemployment rates. When unemployment is high, the supply for labour is traditionally greater than the demand for it, as the number of individuals seeking work significantly exceeds the number of jobs available. Therefore, increasing wages as a means of employers bidding for the service of employees is unnecessary – and so wages remain stagnant during inflation periods. As Venezuela demonstrates, an economy can encounter high inflation alongside low economic growth at one time. Several technical explanations can be proposed with regards to why the country’s economic growth is in deficit. A primary one being the concept of demand-pull inflation which comes about as a result of the demand for goods surpassing the supply available. However, no fundamental increase in aggregate demand was displayed in the case of Venezuela. Instead, the supply fell considerably short. The lack of foreign currency reserves lead to the inability to import fundamental commodities beyond a particular point causing a demand-pull inflation. What’s more, producers increased the prices of their goods and services in order to relay the increased production costs. This is referred to as cost-pull inflation. The lack of ability to secure imports in Venezuela contributed to the rise in production costs. This played a role in the further hindrance of Venezuela’s domestic production (Profolus 2018). Under Maduro’s regulation, the money supply and minimum wage were increased, in attempt to manage consumer spending capabilities, as already discussed. The monetary explanation – is partially applicable when trying to understand the causes of Venezuela’s hyperinflation and it states that the idea of excess money supply with the same amount of goods leads to the decrease in value of a currency.

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