# **7. Conclusion**

We have illustrated how growth regressions can be a useful tool for country-specific policy analysis of growth patterns. Economists performing such analysis will find the data and models presented in our paper a useful reference and can further tailor those to their specific needs (e.g., by exploring further heterogeneities, applying different estimators or model averaging, adding or updating variables). Our reference data can additionally be used by researchers and analysts to explore certain growth-relevant aspects in more detail (e.g., looking at threshold relations or other non-linearities for variables like inflation).

Future research could further improve policy modeling with growth regressions. One apparent angle is to reconsider the dynamic implications of the econometric neoclassical growth model, which assumes that persistence is uniform across countries and variables. Country heterogeneities could easily be addressed with recent advances in the grouped heterogeneity panel econometrics literature (e.g., Bester and Hansen, 2016; Muris and Wacker, 2022). But it may also be necessary to consider alternative dynamic modeling strategies that account for the plausibility that improvements in infrastructure, for example, have more persistent correlations with growth than certain macroeconomic stabilization policies like taming inflation. Another angle worth exploring is to develop metrics that can plausibly compare the relative importance of different policy packages. For example, economists are often curious about the extent to which domestic policies or a favorable external environment can explain a country’s growth episode. Explicit modeling of such relative importance appears futile.<sup>28</sup> Researchers may rather consider using clustering techniques to separate common time-varying shocks in groups of reasonably similar countries (which can then be interpreted as external factors) from variation in growth that is explained by domestic policy variables.

Since our analysis is mostly descriptive and aims to facilitate country-specific growth analysis, future work could also further the identification of peer and reference groups in growth patterns. Moller and Wacker (2017) provide an example by using a cluster analysis to reveal the uniqueness of Ethiopia’s macroeconomic policy mix. The benchmarking of Bangladesh to other top performers in terms of changes in growth correlates in Beyer and Wacker (2023) is another example that could be furthered with more elaborate statistical techniques.

Finally, more research will be needed to better integrate climate aspects into conventional empirical growth models. This includes an integrated assessment of climate vs. growth impacts of different policies, as well as more elaborate modeling of the relationship between climate change and growth. Our dataset can be a fruitful resource for such research.

> 28 In most empirical specifications, the list of “domestic” variables will be more extensive than the set of variables capturing the external environment (see, e.g., Araujo et al., 2016). This will give more explanatory power to the former. It is also not straightforward how to best account for the fact that different countries respond differently to changes in “external” variables.

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