Reference no: EM132225242 , Length: 2250 Words
Research - Economic growth, manufacturing and foreign direct investment
Objective: To examine the association of economic growth with manufacturing and foreign direct investment
Data source: World Development Indicators and World Governance Indicators
1. Describe the data (e.g., mean, standard deviation, skewness, kurtosis, median, max, and min)
2. Prepare correlation matrix
3. Report regression results
4. Write a report stating clearly the objectives of this research, background (i.e., the importance of this research), the hypothesis, analysis of your findings, and the conclusion
Structure of a quantitative research paper
We generally find the following structure in quantitative research papers.
Non-numbered: Abstract
1. Introduction
2. Literature review and hypotheses development
3. Methodology
4. Results
5. Findings and analysis (or discussion)
6. Conclusions
Abstract
An abstract is a short summary (e.g., 150 words) of a research article.1. Introduction
This section discusses the background and motivation of the study. Whilst the primary motivation for academic research comes from the gap in the literature, the need for the study should be made clear. Unless there are some perceived benefits and practical (or policy) implications, there is no need to do a research. Once the importance of the research topic is explained and the gap in the literature is identified, the research question (s) are raised in this section. There might be variation to writing the research questions. Some research mentions the research aims (or objectives) instead of formulating the research questions. Both approaches are very common and accepted.
2. Literature review and hypotheses development
The literature review and hypotheses development section formulates the testable hypotheses to answer the research questions introduced in Section 1. Hypotheses are developed ex-ante (before the data collection) and so it is generally advised that these should be based on the theory or intuitive reasoning rather than grounded on other empirical evidence. It is also suggested to have directional (e.g., positively or negatively related) hypotheses rather than non-directional (e.g., related). Non-directional hypotheses are considered exploratory, for example where theory cannot provide an unambiguous expectation, and so it is better to put effort into developing an ex-ante prediction.
3. Methodology
We need to explain the way the hypotheses will be tested. This section covers the data, model and estimation procedure.
3.1. Data
Sampling and data sources are covered under data.
3.2. Model and estimation procedures
A multiple regression model may appear as follows:
Dependent variable = Intercept + Coefficient (s) x Independent variable (s) + Coefficient (s) x Control variable (s) + Error term
Yi = β0 + βiXi + βiZi + ε
The full form model expression (spelling out each variable) depends on the data structure. For example, if two variables on the right hand side of the equation are highly correlated, we may include only one of these two variables. For this reason, descriptive statistics are provided in the data section.
The estimation procedure depends on a number of factors including the types of variables. For example, if the dependent variable is continuous (i.e., can take on any value within a limit), an ordinary least square regression (OLS) estimation might be suitable. If the dependent variable is dichotomous (i.e., takes on a value of either 1 or 0), a logistic regression (logit) estimation might be appropriate.
4. Results
This section presents the results of the estimation. Generally, the regression outputs are reported in this section. The regression analysis comments on the model fit, explanatory power and statistically significant variables. It also presents additional analyses for robustness.
5. Findings and analysis
Findings of the study are discussed in this section. The discussion involves interpreting the statistical output. More specifically, the discussions should be for a general audience as well as experts in the field. So a non-technical explanation is always useful for a wider audience. The findings are also evaluated by comparing with similar previous studies to position this study in the literature. Economic interpretations (if this can be done) also improve the quality of the research. For example, an increase of $1,000 in payment for attending meeting reduces the meeting non-attendance problem of directors.
6. Conclusions
This section sums up the study. For a reader who is too busy to read the whole paper, this section should provide a summary of the whole paper. It should touch base on the research questions, the hypotheses, the test results, major findings, practical and policy implications, and the contribution of the study.
Attachment:- Data-for-the-group-assignment.rar