## 3 Materials and Methods  
_Lagtp_ represents agricultural TFP indexes (base year 1961 = 100) over 1961-2012 using primarily FAO data; _LRCA_ is the credit to agriculture, in US $, at constant prices, while _LGAO_ is the gross agricultural output for each country, where annual fluctuations have been smoothed by the Hodrick-Prescott filter. The applied analysis uses annual data from 2000 to 2012 for 114 countries, including both developed and developing countries, located in several continents (We gratefully acknowledge the comment of a reviewer who has stressed the importance of exploring the differences across groups of countries. While of great relevance, this is beyond the scope of the present article. In a subsequent analysis, we have shown that the degree of development matters). The data are derived from the World Development Indicator database (see, for more details: [[http://www.econstats.com/wdi/wdic_MNA.htm](http://www.econstats.com/wdi/wdic_MNA.htm)]([http://www.econstats.com/wdi/wdic_MNA.htm](http://www.econstats.com/wdi/wdic_MNA.htm)) (accessed on 1 June 2019)). The data starting period was dictated by credit to agriculture data availability. Moreover, we avoid the more recent years, since the current economic-financial crisis has substantially affected the estimated relationships. We derived the log-transformation of all variables. Table 12 in the Appendix A summarizes the variables considered in the empirical analysis. \begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Author(s)** & **Country** & **Study Period** & **Empirical Strategy** & **Direction of** **Relationships** \\ \hline [PERSON] and [PERSON] (1993) & 80 countries & 1960–1989 & Cross-country regressions & FD \(\rightarrow\) EC \\ [PERSON] and [PERSON] (1995) & 80 countries & 1960–1985 & Cross-country regressions & FD \(\rightarrow\) EC \\ [PERSON] and [PERSON] (1996) & 16 countries & 1960–1993 & Time series & FD \(\rightarrow\) EC \\ [PERSON] and [PERSON] (1996) & Nepal & 1960–1992 & Time series & FD \(\leftrightarrow\) EC \\ [PERSON] and [PERSON] (1996) & 41 countries & 1976–1993 & Cross-country regressions & FD \(\rightarrow\) EC \\ [PERSON] and [PERSON] (1998) & 13 countries & 1970–1991 & Time series & FD \(\rightarrow\) EC \\ [PERSON] and [PERSON] (1998) & 55 countries & 1980–1990 & Cross-country regressions & FD \(\rightarrow\) EC \\ [PERSON] and [PERSON] (1999) & 10 countries & Time series & FD \(\leftrightarrow\) EC \\ [PERSON] et al. (2000) & 63 countries & 1960–1995 & Cross-country and panel data & FD \(\rightarrow\) EC \\ [PERSON] et al. (2000) & 74 countries & 1960–1995 & Cross-country and panel data & FD \(\rightarrow\) EC \\ [PERSON] and [PERSON] (2000) & 47 countries & 1980–1995 & Panel data & FD \(\rightarrow\) EC \\ [PERSON] and [PERSON] (2013) & 109 countries & 1960–1994 & Geweke decomposition test on pooled data & FD \(\leftrightarrow\) EC \\ [PERSON] and [PERSON] (2008) & Korea & 1971–2002 & Time series & FD \(\rightarrow\) EC \\ [PERSON] and [PERSON] (2007) & 74 countries & 1961–1995 & Panel data & FD \(\rightarrow\) EC \\ [PERSON] et al. (2011) & MENA countries & 1980–2007 & Panel data & Mixed results \\ [PERSON] (2013) & 18 African countries & 1960–2001 & Time series & FD \(\leftrightarrow\) EC \\ [PERSON] (2018) & Italy & 1960–2014 & Time series & FD \(\rightarrow\) EC \\ \hline \hline \end{tabular} Notes: EC: Economic Growth; FD: Financial Development. Source: our elaborations.  
\end{table} 
Table 2: Summary of literature between financial development and economic growth. A graphical analysis of the three variables of interest (Figure 1) allows us to conclude overall correlations. The scatterplot matrices show that the gross agricultural output and the agricultural TFP indexes tend to be positively correlated. The relationships of credit to the agricultural sector with the two variables are non-linear.