Running Head: A GEM OF A STUDY 1
A GEM of a Study
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University Name
Instructor Name
September 03, 2021
A GEM OF A STUDY 2
Question 1
Dependent and Independent Variables:
The dependent variable (DV) is very important that is tested or measured in an experiment. The
dependent variable is of interest in all the studies as it measures change and is considered as the
subject of the research. Chittaranjan Andrade stated that “Independent variable (IV) is the one that
cannot be changed and stand-alone”. In this study, the dependent variable is economic growth
measured through jobs and GDP which are correlated to the economic well-being of a country.
We have also noticed that there is also a dependent variable of interest that is business dynamics
that comprises firms/jobs creations, firms/jobs expansion, firms/jobs deaths, and firms/jobs
contractions. The prominent independent variable is activities that most likely stimulate
entrepreneurial activities. We also have noticed several independent variables in the GEM
conceptual model which are general national framework conditions, entrepreneurial framework
conditions, entrepreneurial opportunities, entrepreneurial capacity, and business dynamics. These
independent variables comprise other constructs. The basic aim of this study is to find out the type
of governmental initiatives and policies which are most likely to stimulate entrepreneurship
through GDP and job formation.
Question 2:
This study has manipulated and analyzed several moderating variables (MV) to determine the
effect of the independent variable i.e. governmental initiatives and activities on the dependent
variable i.e. job formation and GDP. This study has used several moderating variables as long as
they are identified as independent variables. GEM authors tried to identify as many moderating
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variables as they can so they can choose the best independent variable which would have a
measurable influence on the dependent variable. These variables are a long-term commitment,
providing resources to women to start the entrepreneurial process, significant post-secondary
education, including training programs intended to cultivate skills needed to start a venture,
cultivating individual’s capacities to explore new opportunities. There are also other variables like
creating a culture to validate and promote entrepreneurship and develop society’s capacity to
compensate for income disparity. Though these variables have considerable influence on the study,
however, these variables could not be statistically measured and researchers have to infer the
effects of these types of variables that is why these are called intervening variables (IVV). Kalton
(1968) stated that “Extraneous variables are treated as moderating or independent variables and
could influence the dependent variables”. We have seen several extraneous variables in general
national framework conditions like openness, social, cultural, and political context which have a
substantial effect on the study but they are not the major focus of the study and we cannot control
their influence. We can control their effect on the results through a casual study.
Question 3
Yes, we can do a casual study without controlling intervening, extraneous, and moderating
variables. However, the results would not be as accurate as by considering those variables. Three
requirements of a casual study are:
1. Empirical Association: As we cannot statistically measure the effects of intervening,
extraneous, and moderating variables, we can measure them through experience and
observation.
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2. Temporal Priority: This means the presence of the extraneous/independent variable
before the introduction of the dependent variable. An example is the existence of the social,
cultural, and political context.
3. Non-spuriousness: This means a statistical relationship between two variables that is
apparently considered due to a causal effect, but upon careful consideration, it is considered
as existing due to coincidence or because of the third intermediary variable. Ashley
Crossman stated that “The best tool for spotting a spurious relationship in research findings
is common sense”. In a study, spuriousness could be controlled from the beginning in a
statistical sense. We can statistically measure the influence of all the other variables that
they could have on the dependent variable to give a vibrant view of the non- spuriousness
(Crossman, 2019).
Question 4
Paul J. Lavrakas asserted that “National experts (key informants) are a proxy for her or his
associates at the organization or group”. They are reliable and trusted experts and have knowledge
of the business environment which helps in conducting the research. They have substantial
knowledge of the entrepreneurial framework conditions. The use of key informants to identify the
entrepreneurial framework conditions of a country permits the researchers to collect indirect
experience and observation of the social, political, and cultural context of the country. This will
help the researchers to control the variations in the geographical environments of the country
(Lavrakas, 2008). Moreover, these experts will provide information about the factors which are
highly correlated with the business start-ups. Thus, they could considerably impact the results of
a study.
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Question 5
Yes, we can do a casual study when primary data collected is ordinal, interval data, or descriptive
opinion. Our study is the example of a descriptive opinion (qualitative study) of the ordinal data
which is represented in statistical terms over a particular period. Descriptive data helps to identify
areas that need further research and also helps to find the variables that can be related. Results of
the descriptive statistics help the researchers to make comparisons, get insights into the samples,
and infer conclusions. It also helps in generalizations and inferences. Pritha Bhandari (2020) stated
“Researchers can search through the ordinal, interval, and descriptive data the significant variables
in a study and can devise a statistically significant hypothesis”.
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References
Andrade, C. (2021 February 26). A Student’s Guide to the Classification and Operationalization
of Variables in the Conceptualization and Design of a Clinical Study, Indian Journal of
Psychological Medicine, 43(2), 177-179.
Bhandari, P. (2021 August, 27). Ordinal Data: Examples, Collection, and Analysis. Scribbr.
https://www.scribbr.com/statistics/ordinal-data/
Crossman, A. (2020 February, 4). What It Means When a Variable Is Spurious. ThoughtCo.
https://www.thoughtco.com/spuriousness-3026602
Kalton, G. (1968). Standardization: A Technique to Control for Extraneous Variables. Journal of
Royal Statistical Society, 17(2), 118-136.
Lavrakas, P. L. (2008). Key Informant. Encyclopedia of Survey Research methods.
