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A: Demand curve depicts the relatioship between price and quantity demanded.
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- Explain what multicollinearity . What are the main problems that multicollinearity creates for OLS estimation results ? Give two ways to detect multicollinearity problem and the hypothesis that are tested ?Determine the share (proportion) of person trips by each of two modes (Private auto and mass transit) using the multinomial logit model and given and following informationConsider the following panel model to examine the effect of retirement on consumption expenditure, consit, of individual i over years t=1,…,3: (B1) log(consit) = β0 + β1retiredit + β2ageit + β3marriedit + β4healthit + δ1Yr2t + δ2Yr3t + ai + uit Where: retiredit is a dummy variable equal to 1 if individual i is retired on year t and 0 otherwise ageit is the individual's age in years marriedit is an indicator variable for whether the individual is married (1) or not (0) in year t healthit is an indicator variable equal to 1 if the individual is in 'good health' and 0 otherwise Yr2 is a dummy variable equal to 1 in year t=2 and 0 otherwise Yr3 is a dummy variable equal to 1 in year t=3 and 0 otherwise We obtain the following results when we estimate Model (B1) using RE and FE methods: Variable Random Effects Fixed Effects retired -0.072*** (0.024) -0.054** (0.025) age -0.008*** (0.003) - married 0.031*** (0.010) 0.028 (0.022) health 0.050*** (0.021) 0.052***…
- Cristina is excited with these averages and tells her public relations team to prepare a glossy brochure to showcase this $250 increase in household income. which of the following must be true to confidently conclude that this $250 difference in average income was caused by access to a UThere The herders who bought UThere phones would have had higher income than the herders who did not even if they had not purchased the UThere phone. The herders who bought UThere phones would have had the same income as the herders who did not even if they had not purchased the UThere phone. We don’t need to worry about Selection Bias since Nepal and Tibet are small countries with more or less similar people. The equation for Selection Bias does not provide enough information since we do not know the counterfactuals.(Econmetrics) Q.1 How can you test for general misspecification of model if it would have only (any of) two independent variables?Given the following data X (consumers of teff) or popn 3 6 8 1 13 13 14 Y ( teff consumption) 8 6 10 12 12 14 20 year 2013 2014 2015 2016 2017 2018 2019 Estimate the regression equation, Y= a+bX, Where Y denotes demand for teff while X is consumers of teff (population) By assuming demand for teff is only affected by its consumers, find the amount demand for teff in the year 2022 if the populations (consumers of teff) are about 18 people? (Hint: use the least square method, parameter a and b can be estimated by solving the two linear equations) SY= na+ bSX SXY=aSX +b Where n is number of years. For example, Estimate the sales for 2012, 2015 and fit a linear regression equation and draw a trend line.ar X Sales (Y) XY X2 year X Sales (Y) XY X2 2002 1 22734 22734 1 2003 2 24731 49462 4 2004 3 31489 94467 9 2005 4 44685 178740 16 2006 5 55319…
- In the December, 1969, American Economic Review (pp. 886-896), Nathanial Leff reports thefollowing least squares regression results for a cross section study of the effect of age composition onsavings in 74 countries in 1964:log S/Y = 7.3439 + 0.1596 log Y/N + 0.0254 log G - 1.3520 log D1 - 0.3990 log D2 (R2= 0.57)log S/N = 8.7851 + 1.1486 log Y/N + 0.0265 log G - 1.3438 log D1 - 0.3966 log D2 (R2= 0.96)where S/Y = domestic savings ratio, S/N = per capita savings, Y/N = per capita income, D1 = percentage ofthe population under 15, D2 = percentage of the population over 64, and G = growth rate of per capitaincome. Are these results correct? Explain..Using Y as the dependent variable and X1, X2, X3, X4 and X5 as the explanatoryvariables, formulate an econometric model for data that is (i) time series data (ii)cross-sectional data and (iii) panel data – (Hint: please specify the specific model herenot its general form).Suppose that the government tends to maximize the tax revenue. How would the cannabis price drop affect the government tax revenue if cannabis was taxed by price? Did the government anticipate the cannabis price drop when designing the tax scheme? You may come up with an artificial numerical example to support your findings. are alcohol and cigarettes substitutes or complements of cannabis?(The answer to this question depends on the actual consumption data. If you do not know the data, you may make an assumption. Then, you should stick with this assumption for the rest of your analysis. For example, if you assume that alcohol and cigarettes are substitutes of cannabis, then your entire analysis is based upon this assumption.) How would the change in the price of cannabis possibly affect the market demand curve for alcohol/cigarettes?
- Without running any additional tests, what can you say about the joint significance of all independent variables in the model? Which statistic(s) helps you to answer this question?I dont understand why my question is being rejected so i'll resend this one. The data is attached in the image. Please help me with these questions. Thank you in advanced!! a. How many observations are included in the data? Is the data balanced?b. Is the above result estimated from the fixed effects model or the random effects model?c. Explain the meaning of the estimate coefficient of the variable ???look at the influence of mileage on the sale price of each brand ofautomobile. Postulate the following statistical models,?_ℎ????? = ?0 + ?1?????? + ?? and ?_?ℎ??? = ?0 + ?1?????? + ?? with ??~?(0, ?2).For each model (‘model_honda’ and ‘model_chev’) perform the following,Comment on the miles variable after examining it with hist() and summary() commands.What does the assumption of non-random independent variable imply about how thedata must be collected if the same miles variable is used for both brand of automobile?