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What are the limitations of quantitative research in evaluating economic development programs?

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Quantitative research is a widely used method of evaluating the impact and effectiveness of economic development programs. It involves collecting and analyzing numerical data to test hypotheses, measure outcomes, and identify causal relationships. However, quantitative research also has some limitations that may affect its validity, reliability, and applicability in different contexts. In this article, you will learn about some of the common challenges and drawbacks of using quantitative research in evaluating economic development programs.

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Rishi Dewan

EY- Economic Policy Group| SBSC, DU'23| FRML1 Formerly: NITI AAYOG| Impact Investors Council| ABSLI| Digi Sidekick
Rebekka Grun von Jolk
Siavash Eftekhari

Financial & Economic advisor to Board of Directors at CinnaGen Co.

1 Data quality and availability

One of the main challenges of quantitative research is ensuring the quality and availability of data. Data quality refers to the accuracy, completeness, consistency, and relevance of the data collected and used for analysis. Data availability refers to the accessibility, timeliness, and adequacy of the data sources and methods. Poor data quality and availability can undermine the validity and reliability of the quantitative research results and lead to erroneous or misleading conclusions. For example, data may be missing, inaccurate, outdated, or biased due to measurement errors, sampling errors, reporting errors, or ethical issues. Therefore, quantitative researchers need to carefully select, verify, and validate their data sources and methods, and address any potential limitations or gaps in their data collection and analysis.

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Rishi Dewan

EY- Economic Policy Group| SBSC, DU'23| FRML1 Formerly: NITI AAYOG| Impact Investors Council| ABSLI| Digi Sidekick
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Quantitative Research often is the basis to test the hypothesis of the researcher. The limitations of quantitative research include the inability to understand complex phenomena, the assumption of deterministic behaviour. Moreover, results suggested by data may not always make economic sense. The issues of statistical analysis can be extended to any economic study/model. The limited options provided to the respondent and the lack of open-ended questions leads to limited and binary outcomes. Consequently, we need to approach the evaluation of any economic development programme by complementing quantitative and qualitative research. This would lead to a more comprehensive understanding and an in depth study of the economic programme at hand.

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2 Contextual and cultural factors

Another limitation of quantitative research is that it may not capture the contextual and cultural factors that influence the outcomes and impacts of economic development programs. Contextual and cultural factors refer to the social, political, environmental, historical, and ethical aspects that shape the behavior, preferences, values, and norms of the participants and stakeholders of the programs. These factors may affect how the programs are designed, implemented, perceived, and evaluated by different groups and individuals. Quantitative research may not be able to account for these factors adequately, as it tends to focus on generalizable and standardized measures and indicators, rather than on the specific and nuanced realities and experiences of the people involved. Therefore, quantitative researchers need to complement their data and analysis with qualitative methods, such as interviews, observations, or case studies, that can provide more depth and insight into the contextual and cultural factors.

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3 Causality and attribution

A third limitation of quantitative research is that it may not establish causality and attribution convincingly. Causality and attribution refer to the causal relationship and the attribution of responsibility between the program inputs, activities, outputs, outcomes, and impacts. Quantitative research aims to test whether the program has caused or contributed to the observed changes and effects, and to what extent. However, establishing causality and attribution can be challenging, as there may be other factors or variables that influence the results, such as external events, confounding factors, or spillover effects. Quantitative research may not be able to isolate or control for these factors or variables, or to measure their effects accurately. Therefore, quantitative researchers need to use rigorous designs, methods, and techniques, such as randomized controlled trials, quasi-experimental designs, or counterfactual analysis, that can enhance the causal inference and attribution of their research.

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Rebekka Grun von Jolk
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If you use an experimental or prospective approach, quantitative methods can assess causality well. What they cannot do is, understand the story behind the cause. For example, you measure absenteeism of public service staff and you realize that people living in the locality are less absent than people living further apart. The deeper reason may be that it’s simply easier to access the services and work there if you live close. Another reason maybe that your neighbors are also your service clients and can hold you accountable. Qualitative research will get at the deeper narrative behind the observed causes and effects. Therefore, it is recommended to use mixed methods, quantitative and qualitative, to triangulate results whenever possible.

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4 Generalizability and applicability

A fourth limitation of quantitative research is that it may not be generalizable and applicable to different settings and situations. Generalizability and applicability refer to the extent to which the research findings and recommendations can be transferred or applied to other populations, contexts, or programs. Quantitative research aims to produce generalizable and applicable knowledge that can inform and improve the design, implementation, and evaluation of economic development programs. However, generalizability and applicability can be limited, as the research may be based on specific assumptions, conditions, or parameters that may not hold true or be relevant in other cases. Quantitative research may also overlook the diversity and heterogeneity of the populations, contexts, or programs, and assume a uniform or average effect or impact. Therefore, quantitative researchers need to acknowledge and address the limitations and assumptions of their research, and to contextualize and adapt their findings and recommendations to different settings and situations.

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5 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Siavash Eftekhari

Financial & Economic advisor to Board of Directors at CinnaGen Co.
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Quantitative research faces significant limitations in assessing economic development programs due to its incapacity to fully encompass the intricate realities of real-world situations. The involvement of multiple interacting factors in such programs poses a challenge in isolating the specific impact of one program through quantitative data, potentially leading to misleading conclusions about effectiveness. Another drawback is the assumption of deterministic economic behavior, disregarding influences like social norms, cultural values, and government policies that are challenging to quantify accurately.

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What are the limitations of quantitative research in evaluating economic development programs?

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3

4

5

1 Data quality and availability

2 Contextual and cultural factors

3 Causality and attribution

4 Generalizability and applicability

5 Here’s what else to consider

Economics

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What are the limitations of quantitative research in evaluating economic development programs?

1

2

3

4

5

1 Data quality and availability

2 Contextual and cultural factors

3 Causality and attribution

4 Generalizability and applicability

5 Here’s what else to consider

Economics

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