Decisionmaking is crucial in corporate and business sectors. Many indicatorsare used to make the decision through data analyses. This paper aimsto illustrate how careful assessment and understanding of datathrough econometrics is an important part of decision making inbusiness and governmental entities. is defined as thestatistical methods used to assess data and use the information tomake informed decisions ("Acknowledgement to Reviewers of in 2015," 2016).
Analyzingof goods and services production is important in the nation`seconomic sphere. It will be necessary to evaluate the data relatingto the manufacture of products and services to make the decision onthe supplying of goods and services (Raghuvanshi, 2016). Thereleasing of the October, 2016 goods and services deficit by theU.S. BEA analysis and Census Bureau, in partnership of the CommerceDepartment, declared a $42.6 billion increase from the last Septemberdata which was $36.2 billion. The figure indicated reduction by $3.4bringing it to a possible $186.4 billion.
TheOctober goods import were more $229.0 slightly more than the previousyear by $3.0 billion. by Such information is necessary fordetermining the imports and exports of goods, for instance, a companywill make an informed decision on whether to import or to export inthe face of linear regression. Due to the reduced shipping, thebusiness group will decide to ship goods because of the created gap.In the released information, October also showed an increase inproperties and services offered indication a consumption increase of$6.3 billion bringing the figure to $63.4 billion. It will also showa decrease in the services surplus offered of $0.1 billion to $20.8billion (Chamberlain, 2011).
Theincrease in the services provided indicates that there is a propermanagement of the services and therefore the business will opt forthe advertisement of their offered services. In early January, therewas a deficit of goods and services offered of about 2.1 percent.This was indicated by $8.8 billion, which is yet a drop further by3.0 percent bringing $67.0 billion. The displayed data will indicateother implications such as the areas to supply more products, whetherto use advertisement and general management of the supply andproduction of goods and services.
Lastthree month, there was a significant improvement of $1.0 to 39.8billion. The increase has also showed an improvement of theproduction of goods and services by $0.1 billion. Also, in the samemonth, average import of goods and services improved by $1.0 billionto $227.8 billion (Chamberlain, 2011).
Theprimary tool used in the econometrics in decision making is thelinear regression models. It provides the basic approach used inestimating how a change in one business or economic variable, whichis always the explanatory variable, affects the next variable whichis used in the comparison. It is called the dependent variable("Finance & Development," 2016). It will be workablewhen taking into account the influence of all the other determinantsof the other related dependent variable.
Inconclusion, this qualification of the linear regression issignificant because it seeks to aim the marginal effect of aparticular explanatory variable, such as population, after takinginto account the impact of the other explanatory variables in themodel like salary and supply of goods. For example, the model mayisolate the incidence of a one percentage point increase in goods orservice usage on average household expenditure, holding constantother determinants of consumption, such as wealth, pretax income, andinterest rates.
Acknowledgementto Reviewers of in 2015. (2016). ,4(1),5. http://dx.doi.org/10.3390/econometrics4010005
Chamberlain,G. (2011). and decision theory. JournalOf ,95(2),255-283. http://dx.doi.org/10.1016/s0304-4076(99)00039-1
Finance& Development.(2016). Finance& Development | F&D.Retrieved 14 December 2016, fromhttp://www.imf.org/external/pubs/ft/fandd/basics/econometric.htm
Raghuvanshi,M. (2016). Knowledge and Awareness: Linear Regression. EducationalProcess: International Journal,5(4),279-292. http://dx.doi.org/10.22521/edupij.2016.54.2