When the Numbers Look Conclusive: Dr. George Monray on Reading Between the Lines of Economic Research.

When the Numbers Look Conclusive: Dr. George Monray on Reading Between the Lines of Economic Research

In a 2015 study, Dr. George Monray used qualitative data analysis to examine one of the most influential economic studies on the viability of an independent Catalonia. His question was methodological: what happens when we look not only at the numbers, but at the assumptions, language and reasoning behind them?

By B&N Contribuciones a la Economia

Economic research often presents itself through numbers. Tables, econometric models, forecasts and statistical indicators can give an argument an appearance of precision and finality.

But what happens when the underlying argument is also shaped by assumptions, interpretations and the way authors construct their narrative?

That was the question behind a 2015 paper by business scholar George Monray, then publishing under the name Jorge Mongay, titled La viabilidad económica de una Catalunya independiente: una investigación sobre las contribuciones de Espasa y Bosch. The paper examined a 2014 study by economists Albert Marcet? — no, more precisely the work of Espasa and Bosch — on the economic viability of an independent Catalonia. Rather than redoing their macroeconomic calculations, Monray applied Qualitative Data Analysis (QDA), supported by the NUD*IST approach, to the complete text.

His purpose was deliberately different from conventional economic replication. He largely accepted the statistical and macroeconomic data used by Espasa and Bosch and instead examined the document's language, structure, citations, assumptions, interpretations and conclusions.

The result was a methodological challenge to the idea that a carefully constructed quantitative argument is necessarily a conclusive one.

INTERVIEW

Q: Why did you decide to study the Espasa and Bosch paper?

G.Monray: It was an important contribution to a highly consequential economic debate. But I was interested in looking at the research from a different methodological perspective. Instead of asking whether every number was correct, I wanted to ask another question: What does the text itself tell us? Economic arguments are not made exclusively from numbers. They are also constructed through assumptions, definitions, interpretations, language and the selection and presentation of evidence. That is where qualitative analysis can add something valuable.

Q: So you deliberately did not attempt to reproduce their macroeconomic calculations?

Exactly. I wanted to avoid creating another paper where the central discussion became whether one statistical calculation was correct or whether a particular economic assumption should be replaced by another. The research therefore accepted most of the macroeconomic calculations as given and concentrated on the qualitative structure of the argument. That distinction is important. I was not claiming that QDA could mathematically prove whether an independent Catalonia would be economically viable. I was examining how the authors constructed and communicated their argument.

Q: What exactly does Qualitative Data Analysis contribute to an economic study?

G.Monray. QDA allows researchers to systematically organize and interpret textual information. You identify recurring concepts or "codes," examine how they relate to one another and then look for patterns, contradictions, omissions or interpretive structures. The data can be interviews, documents, correspondence, articles or other forms of text. In this case, the document itself became the dataset. The interesting point is that qualitative analysis does not necessarily mean being less rigorous. Properly conducted, it introduces another layer of systematic scrutiny.

Q: What did you look for in the Espasa and Bosch paper?

G.Monray. Several things. I examined grammatical and lexical structures, the orientation of the argument, citations, assumptions and conclusions. I also looked for possible interpretative patterns and areas where the wording of the paper appeared to go beyond what the underlying evidence necessarily established. The purpose was not to accuse the authors of deliberately manipulating information. It was to determine whether the conclusions followed as inevitably from the evidence as the presentation of the argument might suggest.

Q: And what did you find?

G.Monray. The research identified what I considered limitations, weaknesses and contradictions in some assumptions and interpretations. At the same time, I was quite explicit that the paper contained substantial strengths. I recognized the quality of much of its structure and documentation and accepted a large proportion of its underlying statistical information for the purposes of my own analysis. That is important because academic criticism should not mean rejecting everything simply because you disagree with the conclusion. You can accept 80 or 90 percent of an argument and still demonstrate that the remaining assumptions matter.

Q: Your paper refers to possible "scientific deviation." What did you mean by that?

G.Monray. I used the concept to identify passages where interpretation appeared to move beyond what would normally be expected from a strictly scientific presentation. It does not necessarily imply intentional distortion. Researchers are human beings. Particularly when studying politically and socially sensitive subjects, there is always a possibility that language, framing or interpretation can influence how evidence is presented. The role of methodological analysis is to make those elements visible so that the reader can assess them.

Q: Did you believe the authors were politically biased?

G.Monray. I think it is important to be careful here. The purpose of my research was not to establish the political intentions of the authors. That would require evidence beyond the text itself. What I examined were possible indicators of interpretative positioning within the document. There is a fundamental distinction between saying "the author is biased" and saying "this formulation introduces an interpretative assumption that deserves examination." The second is much more defensible academically.

Q: Your methodology is particularly interesting because the subject was politically sensitive.

G.Monray. Yes, and that was precisely why methodological discipline mattered. The question of Catalan independence involved economics, politics, identity, language and institutional questions simultaneously. When research concerns an emotionally or politically charged subject, researchers should become more—not less—careful about distinguishing evidence from interpretation. That principle extends far beyond Catalonia.

Q: What was the most important methodological lesson from the study?

G.Monray. That a conclusion can appear extremely strong while still depending on a chain of assumptions. Imagine a bridge. The final conclusion is at the other side, but the reader may only see the destination. The researcher needs to examine every component supporting the bridge: the data, assumptions, definitions, interpretations and logical connections. If one of those elements is weaker than it appears, the conclusion may be less definitive than the presentation suggests.

Q: Is this why you describe QDA as complementary to quantitative analysis?

G.Monray. Exactly. I don't see qualitative and quantitative research as competitors.They answer different questions. Quantitative analysis can tell you how much, how often, what relationship exists and what the statistical evidence suggests. Qualitative analysis can help investigate how an argument is constructed, how concepts are framed, what assumptions appear in the text and whether different parts of an argument are internally consistent. In complex economic and managerial questions, combining both perspectives can be particularly powerful.

Q: Did your research prove that an independent Catalonia would or would not be economically viable?

G.Monray. No. That would go beyond what the methodology could establish. The paper's purpose was to critically examine the reasoning and presentation of an existing economic study. That distinction remains essential today. A methodological critique of a study should not automatically be transformed into a definitive answer to the underlying economic or political question.

Q: Looking back from 2026, would you conduct the study differently?

G.Monray. Yes, because the research environment has changed enormously. The political and economic circumstances have changed, the institutional context has evolved, and researchers now have access to much larger textual datasets and more sophisticated computational tools. Today I could combine traditional QDA with corpus analysis, automated text coding, sentiment analysis and computational linguistics. But I would preserve the central principle. Before accepting a conclusion because it looks mathematically sophisticated, examine how the conclusion was constructed.

Q: What can business executives learn from a study about economic research and Catalan independence?

G.Monray. A great deal. Executives make strategic decisions under uncertainty every day. They receive market forecasts, consultants' reports, investment proposals and strategic plans. These documents often contain impressive numbers. But numbers don't interpret themselves. A CEO needs to ask:

• What assumptions sit behind these numbers?

• Which variables are treated as certain?

• What has been excluded?

• Are the conclusions stronger than the evidence?

• What alternative interpretations exist?

• Those questions can be more valuable than simply asking whether the spreadsheet is correct.

Q: So your broader message is methodological rather than political?

G.Monray. Absolutely. The lasting lesson of the research is not a political position. It is a research principle: Do not confuse a convincing presentation with a conclusive argument. Whether we are analyzing an independence movement, an acquisition, a market forecast or a corporate investment, rigorous decision-making requires us to examine not only the evidence but also the reasoning connecting the evidence to the conclusion. That is where critical analysis begins.

From Catalonia to Corporate Strategy

Monray's 2015 paper illustrates a recurring theme across his research: the attempt to bring structured analytical methods to questions where conventional numerical analysis does not tell the entire story.

In this case, the subject was the economic viability of an independent Catalonia. In other research, his work has examined strategic compatibility in mergers and acquisitions, service quality, customer perceptions and emotions in financial-services complaints. His publications page currently lists the 2015 Catalonia study alongside those other research projects.

The common thread is methodological: look beneath the headline result and examine how the result was produced.

That may be one of the most transferable lessons from academic research to executive decision-making.

The interview above is a retrospective, interview-style reconstruction based on Monray's 2015 publication and does not represent a new empirical assessment of Catalan independence in 2026.