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An important feature of a modern approach is that the explanatory variables—along with the dependent variable—are treated as correct answers outcomes of random variables Econometrics is based upon correct answers the development of statistical methods for estimating economic relationships, ...

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  • Introductory Econometrics Wooldridge || with Accur
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Introductory Econometrics Wooldridge || with Accurate
Answers 100%.
An important feature of a modern approach is that the explanatory variables—along with the
dependent variable—are treated as correct answers outcomes of random variables

Econometrics is based upon correct answers the development of statistical methods for
estimating economic relationships, testing economic theories, and evaluating and implementing
government and business policy.

A common application of econometrics is the forecasting of such important macroeconomic
variables as interest rates, inflation rates, and gross domestic product (GDP)

Nonexperimental data correct answers are not accumulated through controlled experiments on
individuals, firms, or segments of the economy. (Nonexperimental data are sometimes called
observational data, or retrospective data, to emphasize the fact that the researcher is a passive
collector of the data.)

Experimental data are correct answers often collected in laboratory environments in the natural
sciences, but they are more difficult to obtain in the social sciences. Although some social
experiments can be devised, it is often impossible, prohibitively expensive, or morally repugnant
to conduct the kinds of controlled experiments that would be needed to address economic issues

An empirical analysis uses correct answers data to test a theory or to estimate a relationship.

How does one go about structuring an empirical economic analysis? correct answers It may seem
obvious, but
it is worth emphasizing that the first step in any empirical analysis is the careful formulation of
the question of interest. The question might deal with testing a certain aspect of an economic
theory, or it might pertain to testing the effects of a government policy. In principle, econometric
methods can be used to answer a wide range of questions.

In some cases, especially those that involve the testing of economic theories, a correct answers
formal economic
model is constructed

An economic model consists of correct answers mathematical equations that describe various
relationships

Job Training and Worker Productivity correct answers In this case, there is little need for formal
economic theory. Basic economic understanding is sufficient for realizing that factors such as
education, experience, and training affect worker productivity. Also, economists are well aware
that workers are paid commensurate with their productivity. This simple reasoning leads to a
model such as

,Again, other factors generally affect the wage rate, but equation (1.2) captures the essence of the
problem.

After we specify an economic model, we need to turn it into correct answers what we call an
econometric model

how an econometric model relates to an economic model. correct answers Take equation (1.1) as
an example. The form of the function f(.) must be specified before we can undertake an
econometric analysis. A second issue concerning (1.1) is how to deal with variables that cannot
reasonably be observed. For example, consider the wage that a person can earn in criminal
activity. In principle, such a quantity is well defined, but it would be difficult if not impossible to
observe this wage for a given individual. Even variables such as the probability of being arrested
cannot realistically be obtained for a given individual, but at least we can observe relevant arrest
statistics and derive a variable that approximates the probability of arrest. Many other factors
affect criminal behavior that we cannot even list, let alone observe, but we must somehow
account for them

The ambiguities inherent in the economic model of crime are resolved by specifying a particular
econometric model: correct answers The choice of these variables is determined by the economic
theory as well as data considerations. The term u contains unobserved factors, such as the wage
for criminal activity, moral character, family background, and errors in measuring things like
criminal activity and the probability of arrest

We could add family background variables to the model, such as number of siblings, parents'
education, and so on, but we can never eliminate u entirely.

In fact, dealing with this error term or disturbance term is perhaps correct answers the most
important component of any econometric analysis

The constants b0, b1, . . . , b6 are correct answers the parameters of the econometric model,and
they describe the directions and strengths of the relationship between crime and the factors used
to determine crime in the model.

A complete econometric model for Example 1.2 might be correct answers where the term u
contains factors such as "innate ability," quality of education, family background, and the myriad
other factors that can influence a person's wage. If we are specifically concerned about the
effects of job training, then b3 is the parameter of interest.

For the most part, econometric analysis begins by correct answers specifying an econometric
model, without consideration of the details of the model's creation

In the economic model of crime example, we would start with an econometric model such as
(1.3) and use correct answers economic reasoning and common sense as guides for choosing the
variables. Although this approach loses some of the richness of economic analysis, it is
commonly and effectively applied by careful researchers.

, A cross-sectional data set correct answers consists of a sample of individuals, households, firms,
cities, states, countries, or a variety of other units, taken at a given point in time

An important feature of cross-sectional data is that we can often assume that they have been
obtained by random sampling from the underlying population

Sometimes, random sampling is not appropriate as an assumption for analyzing cross-sectional
data. correct answers For example, suppose we are interested in studying factors that influence
the accumulation of family wealth. We could survey a random sample of families, but some
families might refuse to report their wealth. If, for example, wealthier families are less likely to
disclose their wealth, then the resulting sample on wealth is not a random sample from the
population of all families. This is an illustration of a sample selection problem

Another violation of random sampling occurs when we correct answers sample from units that
are large relative to
the population, particularly geographical units. The potential problem in such cases is that the
population is not large enough to reasonably assume the observations are independent draws

For example, if we want to explain new business activity across states as a function of wage
rates, energy prices, corporate and property tax rates, services provided, quality of the workforce,
and other state characteristics, it is unlikely that business activities in states near one another are
independent.

For the most part, we will ignore the intricacies that arise in analyzing such situations and treat
these problems in a random sampling framework, even when it is not technically correct to do so

The fact that the ordering of the data does not matter for econometric analysis is correct answers
a key feature of cross-sectional data sets obtained from random sampling.

A time series data correct answers set consists of observations on a variable or several variables
over time

Because past events can influence future events and lags in behavior are prevalent in the social
sciences, time is an important dimension in a time series data set. Unlike the arrangement of
cross-sectional data, the chronological ordering of observations in a time series conveys
potentially important information.

A key feature of time series data that makes them more difficult to analyze than cross-sectional
data is that economic correct answers observations can rarely, if ever, be assumed to be
independent across time. Most economic and other time series are related, often strongly related,
to their recent histories. For example, knowing something about the GDP from last quarter tells
us quite a bit about the likely range of the GDP during this quarter, because GDP tends to remain
fairly stable from one quarter to the next

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