Level of development, foreign direct investment and domestic investment in food manufacturing

Background: Whilst the literature on the complementarity and substitutability of foreign direct investment (FDI) on domestic investment (DI) is not uncommon, the facet of food manufacturing is non-existent. This paper fills this void by investigating the effect of FDI on DI in the food manufacturing sector for developing, economies in transition and developed countries. Methods: Using an unbalanced panel data of 49 countries from 1993 to 2016, from FAOSTAT, estimated by the system generalised method of moments (GMM), the Wald statistics for the short and long-run effects of FDI on DI were computed for the development groups. Results: Developed economies experienced a crowd-out effect of FDI on DI in the short run, whilst the others experienced no significant effect. In the case of the long run, the food manufacturing sectors of all three development groups exhibited a crowd-out effect. The effect in the long run for all development groups together is a crowd-in. Analysing all country groups together could mask the results of the various country groups. Conclusions: A review of investment policies to prioritise FDI entry mode that favour domestic investment is needed. Improvement of the investment regulatory and administrative efficiency among others are recommended.

Global gross domestic product (GDP) of food manufacturing for 2017 is estimated at US$1.68 trillion (FAOSTAT, 2020). The sector appears to be relatively more important to developing and economies in transition as it constitutes 3.03% and 3.11% respectively of GDP than developed countries (2.10%) (FAOSTAT, 2020) 1  Whilst the cross-country studies focused on whole economies, these were limited to transition, developing, or developed and developing countries. The single-country studies failed to address the effect of FDI on DI for food manufacturing. This paper fills these gaps by investigating the effect of FDI on DI in the food manufacturing sector for developing, economies in transition and developed countries.
The implications of the effects of FDI inflows on DI are issues that require increased attention by international economists and the facet of food manufacturing concerns agricultural economists as well. Analysing this topic requires linking development and investment theories within the food manufacturing sector. Understanding the issues surrounding the effect of FDI on DI in the food manufacturing sector across countries at varying levels of development is essential in understanding short-and long-term adjustments facing investors and economic managers as food systems become more integrated into the global economy.
In what follows, the existing theories and empirical evidence regarding the effect of FDI on DI are presented. The section on results and discussions is preceded by the outline of the data, modelling and estimation procedure. The conclusions and recommendations complete the paper.

Relevant theories
In line with the key issues in the paper, the theoretical review is constituted into four parts. The first, theories of development seek to explain the differences in the level of development of countries, one of the foci of the paper. Space is provided for FDI theories as these explain the role of the key variable that influences DI. DI is the dependent variable and thus deserves space, hence the investment theories. To tie in, in the interaction of FDI and DI, the theoretical explanation of the link between FDI and DI is outlined as well.
Many theories have been propounded regarding economic development. These have been classified differently. The classification used here is modernisation, dependency, world systems and globalisation. Modernisation theory uses a systematic process to move underdeveloped countries to a more sophisticated level of development (Reyes, 2001). This theory which stresses the importance of political development in the progress and climactic improvement of a nation's economic standing, also acknowledges social and cultural reforms. Further, it seeks to explain inequality within or between states by identifying different values, systems and ideas held by different nations (Martinussen, 1997). Also, it gives attention to the shift of modern technology and development institutions and labour habits complementary to industrial production (Chase-Dunn, 1975).
Dependency theory seeks to improve modernisation theory, combines elements from a neo-Marxist theory and adopts a revolution of underdeveloped nations model (Reyes, 2001). This, together with the Marxist position seeks to explain the origin of surpluses, the basis of theoretical evaluation of progress, and inequality. The divide between developed and under-developed countries is well established. The reason for the difference between the divide and what interventions are required to 1 The estimates include tobacco. The "World System" is multiple cultural systems with a single division of labour. The basic feature of this system is having a pool of labour in which different divisions and areas are dependent upon each other in exchanging the provisions of those areas (Wallerstein, 1974). In using other levels of quantitative analysis, this theory argues that international trade specialisation and transfer of resources from less developed countries to developed countries prevents development in less developed countries by making them rely on core countries and by encouraging peripheralisation (Szymanskiv, 1982). The theory views the world economy as an international hierarchy of unequal relations. Through the world system, a country can change its position in the global hierarchy (Szymanskiv, 1982).

Amendments from Version 2
Globalisation as a theory of development uses a world mechanism of greater integration with emphasis on the sphere of economic transactions (Reyes, 2001 Foreign direct investment theories can be viewed from three perspectives. The first perspective, which is internationalisation theory, explains why firms often prefer FDI to license as a strategy for entering a foreign market (Hymer, 1976). In this theory, FDI is preferred for licensing and exporting. Licensing may result in a firm giving away valuable technological expertise to a potential foreign investor at a fee. This does not give a firm control over manufacturing, marketing, and strategy in a foreign country that may be required to maximise its profitability. Unfortunately, the competitive advantages of management, marketing, and manufacturing capabilities are not amenable to licensing.
The second perspective relates to the patterns of FDI. In oligopolistic industries, firms invest in other countries as a strategy by following their domestic competitors (Knickerbocker, 1973). Related to this is the product life cycle hypothesis (Vernon, 1966). Firms invest in other advanced countries when local demand in those countries grows large enough to support local production. Production is subsequently shifted to developing countries when product standardisation and market saturation give rise to price competition and cost pressures.
The third perspective is the Dunnings' eclectic paradigm. Dunning (1977); Dunning (1988); Dunning (2001) stated that the extent, geography, and industrial composition of foreign production undertaken by the multinational enterprise is determined by the interaction of three sets of interdependent variables which, themselves, comprise the components of three sub-units, namely; ownership, location and internationalisation (OLI). All other factors unchanged, the greater the competitive advantages of the investing firms, relative to those of other firms, the more they are likely to be able to engage in or increase, their foreign production. This is the own competitive advantage. For the location, the more the immobile, natural or created endowments, needed by the firms to use jointly with their competitive advantages, favour a presence in a foreign rather than a domestic location, the more firms will choose to supplement or take advantage of their own specific advantages by engaging in FDI. The multinational enterprise, thus, would undertake activities to add value to its operations. Internalisation, the final competitive advantage, offers a framework for evaluating alternative ways in which firms may organise the creation and exploitation of their core competencies. These range from buying and selling goods and services in the open market, through a variety of inter-firm non-equity agreements, to the integration of intermediate product markets and outright purchase of a foreign corporation.  and Kejžar (2016) reported switching effects of FDI on DI for transition economies; short-run crowding-out effect to long-run crowding-in effect. The magnitude of the possible linkage and spillover effects over time overcomes the initial competition effect. Also, the period for the long run is such as would allow completed plants to run for some time to generate output and associated benefits. Technology, knowledge transfer, employment and expenditure on social responsibility would come to fruition.
Gallova (2011) reported that FDI exerted no effect on DI for Bulgaria and Romania but crowding in effect for Croatia and Slovenia. For the Balkans, for the period 1993-2009, the effect was crowding out. Gallova (2011) explained that foreign companies do employ the services of the same suppliers as their parent companies that are not in the host country. MNEs tend to also bring with them to the host country, foreign producers from which they take the components necessary for their production. Additionally, foreign-owned companies are so strong in individual sectors and effectively functioning. When domestic firms fail to assert themselves effectively and establish cooperation with MNEs they tend to be crowded out of the market. In the long run, however, based on the panel data from 1993-2009, Gallova (2011)  From the empirical review, some studies dwelled on whole economies across countries whilst others covered one or single economy. One single economy study addressed agriculture. Food manufacturing, the offtaker of agricultural production and the product supplier for marketing in the agribusiness value chain, has not been given attention. This paper focuses on this.

Domestic investment into food manufacturing
Gross fixed capital formation of food manufacturing divided by food manufacturing value-added both in current US$

DI_1
Domestic investment into food manufacturing with a one-year lag Gross fixed capital formation of food manufacturing divided by food manufacturing value-added with a one-year lag both in current US$

DI_2
Domestic investment into food manufacturing with a two-year lag Gross fixed capital formation of food manufacturing divided by food manufacturing value-added with a two-year lag both in current US$

FDI
Foreign direct investment into food manufacturing Foreign direct investment into food manufacturing is divided by food manufacturing value-added both in current US$

FDI_1
Foreign direct investment into food manufacturing with a one-year lag Foreign direct investment into food manufacturing is divided by food manufacturing value-added with a one-year lag both in current US$

FDI_2
Foreign direct investment into food manufacturing with a two-year lag Foreign direct investment into food manufacturing is divided by food manufacturing value-added with a two-year lag both in current US$

GR_1
The growth rate of food manufacturing with a one-year lag The growth rate of food manufacturing value-added at 2010 prices with a one-year lag

GR_2
The growth rate of food manufacturing with a two-year lag Where ε I,t is the error term.
To account for the levels of development of the countries in the data, for which reason the effects of FDI on DI may differ, Equation 1 is re-specified: All the variables and their sources are described in Table 2. The classification of countries based on the level of development reflects the basic conditions (United Nations, 2020). It does indirectly capture some macroeconomic variables that could otherwise have been included as control variables.
Let β STk be the short-run effects, where k=1,2, 3,4 are developing countries, economies in transition, developed countries and all development groups, respectively. Then, for developing countries.
In the case of transition economies, Whilst for developed countries, For the three-country group effects, the null hypothesis for the short run is Failure to reject these null hypotheses with a chi-square test implies FDI has no short-run or contemporaneous effect on DI. Rejection of the null hypothesis and that β STk > 0 means a contemporaneous crowd-in effect of FDI on DI. Alternatively, β STk < 0 means a contemporaneous crowd-out effect of FDI on DI.
The long-run effect is represented by c. Now, consider the case that the null hypothesis, ˆL TK β = 1 is rejected and ˆL TK β < 1, there is then a long-run crowd-out effect. One additional currency unit of FDI leads to less than one currency unit increase in total investment. This means there is a displacement of DI by FDI. . GMM has some weaknesses. First, in the presence of the lagged dependent variables on the right-hand side of the equation and the time-invariant country-specific factors, the fixed-effects estimator would yield inconsistent estimates because of the correlation between the lagged dependent variable and the error terms. Taking the first differences to remove the time-invariant country-specific factors still results in a correlation between the error term and the DI. Second, FDI inflows are likely to be endogenous and determined jointly with the DI. Impliedly, there is a two-way relationship between DI and FDI (Al-sadiq, 2013; Arellano & Bond, 1991; Arellano & Bover, 1995). The system-GMM estimator enables controlling for the unobserved country-specific factors and solves the correlation problem by using a set of internal instruments based on the assumption of no second-order serial correlation in the first-differenced idiosyncratic errors, and the independent variables are weakly exogenous. In this way, the estimated coefficients would then not be subject to bias from an omitted variable. Using a series of internal instrumental variables based on lagged values of the dependent and independent variables, the system-GMM estimator solves the endogeneity problem as well. All these are accomplished by combining in one system, the regression in differences with the regression in levels under the assumption that there is no correlation between the differences of the righthand side variables and the unobserved country-specific effects (Al-sadiq, 2013; Arellano & Bond, 1991; Arellano & Bover, 1995; Blundell & Bond, 1998). The assumption of no serial correlation is testable. Whilst first-order autocorrelation (AR(1)) of the errors is permissible, that of the second-order (AR(2)) is inadmissible. As internal instruments are used, the Sargan test tests whether the overidentifying restrictions are valid. Rejection of the null hypothesis would indicate that the instruments are not valid, therefore, the estimates are not reliable.

Results and discussion
Summaries Due to the unbalanced nature of the panel, the number of observations for the variables is not the same. The observations ranged from 611 to 1,344. The growth rate (GR) for food manufacturing value-added averaged about 3% ( Table 3). The means of DI_1 for developing, transition and developed economies were respectively, 0.0369, 0.0079 and 0.1083. These are statistically distinguished (Table 4). Thus, developed countries on average accumulate about 11% of food manufacturing domestic investment as GDP whilst developing countries manage about 4%. Economies in transition posted less than 1%. The positive value of FDI implies that there has been a transfer of FDI from one economy to the other. This is symptomatic of international capital transfer (Dunning, 1977;Dunning, 1988;Dunning, 2001;Reyes, 2001). The means of FDI_1 of the development groups is likewise statistically distinguished. However, the values constitute less than 1% of food manufacturing value-added. As in the case of DI, developed countries post a higher value of 0.99%. Transition economies, however, seem to attract more FDI dollars of food manufacturing GDP than developing economies.
As the key variables are FDI and DI, linear correlation coefficients were computed (second panel of Table 4). There is a significant positive correlation between FDI and DI for each developing country group. For the country groups together, however, the positive relationship is not statistically distinguishable from zero. Similarly, in the long run, there are positive significant relationships between FDI and DI but no significant relationship for all country groups. Although the linear correlation coefficients could give an early indication of the effect between the variables, the influence of other variables during the estimation process could change the effect shown by the linear correlation coefficient.

Sensitivity analysis
Up to 15 lags were estimated for the system GMM. This is because the lag length is known to influence the size of estimates especially, coefficients and standard errors, which are crucial in the calculation of the short and long-run effects of FDI on DI. Based on the number of significant coefficients and the level of significance lag 4 was selected. The selected system GMM results are reported in Table 5 as model 4.    As the goal of the estimations is to ascertain the short and long-run effects of FDI on DI, the estimates of models 1 -5, were used to compute the effects (Table 6). The short and long-run effects are consistent across all five models for developing and developed economies and for the long run for economies in transition. The only departures are for the short run in the case of transition economies; statistically significant effects for model 1 and model 3. This is not surprising. Transition economies in the data are made up of three countries; Armenia, Kazakhstan and the Russian Federation (Table 1). Thus, the results of the group are more likely to be responsive to the deletion and inclusion of variables and observations than those country groups with larger numbers. Combining all the country groups, the short-run effects for model 1 differ from those of other models. Also, the statistics of the long-run effect of model 5 are statistically insignificant, unlike others that are statistically significant, although the magnitude is like others. Model 5 has two coefficients that were statistically insignificant more than the other models, suggesting high standard errors. This certainly contributed to the statistically insignificant Wald statistic. Overall, however, the results of the short and long-run effects are generally consistent and robust to the estimations of model 4, the standard.

Discussion of estimations
The AR(1) (Autoregressive 1) and AR(2) (Autoregressive 2) statistics fall within expectations, with first-order serial correlation with no second-order serial correlation (Table 7). The Sargan statistics are also statistically insignificant. That is the failure to reject the null hypothesis that the instruments are not valid. Impliedly, the estimates are reliable.   The positive and statistically significant TIME coefficient suggests annually, the ratio of DI to GDP in food manufacturing increases by 0.09% (Table 7). Thus, although the countries in the development groups have significantly different levels of DI, collectively, the DI is rising. This is in line with the notion that current years' investments are explained by previous years' investments (Hall & Jorgensen, 1967). This contrasts with the negative coefficient for whole economies of developing countries (Agosin & Machado, 2005) and developed countries (Wang, 2010). Both the one-and two-year lags of growth of food manufacturing value-added coefficients suggest for unit increases GR_1 and GR_2, the DI ratio increases by at least 2%. This is expected as increased income from food manufacturing can be channelled into savings. This would then become investable funds for the sector. This result also confirms the theoretical position that the level of output is one of the drivers of the investment function (Jorgenson, 1963).
The dynamic effects of FDI on DI are presented in Table 8. The null hypothesis that the statistic of 0.0056 is different from  In the case of the long run, the null hypothesis that the Wald statistic value of 0.3711 is indistinguishable from 1 was rejected at a chi-square value of 9.16. Since the statistic is less than 1, there is a crowd-out effect in the long run for developing country food manufacturing. For a one-dollar increase in FDI in food manufacturing, DI in the food manufacturing sector increases by 0.37 (less than one dollar). This is like the findings For economies in transition, the results are akin to that of the developing countries; no effect in the short run and crowd-out effect in the long run. The exception is that the statistics are larger than those of the developing countries. This suggests the extent of crowding out is less severe for transition economies than for developing economies. In the case of the long run, one-dollar increase in FDI will lead to 0.64 dollars (less than one dollar) increase in DI in the food manufacturing sector. Whilst the short-run result agrees with Jude (2019) and Kejžar (2016), it departs from that of Mileva (2008), who found a crowd-in effect for transition economies. However, in the long run, Mileva (2008) found a neutral effect for transition economies.
Turning to developed countries, there is crowd-out for both short-run and long-run effects. For the latter effect, one dollar increases in FDI into food manufacturing results in a decrease of 0.015 dollars in DI. Crowd-out estimates with negative values are more detrimental than those with positive values. In the case of the former, there is an actual decrease in DI whilst for the latter, the magnitude is an increase albeit less than one. The short-run crowd-out found for food manufacturing in developed countries agrees with that found by Wang (2010) for the whole economy of developed countries. Whilst the short-run result departs from those of the developing and transition economies, that for the long run is similar. Further, the coefficient for the long run is slightly higher than that of economies in transition. This result is like that of Mišun & Tomšík Some reasons can be adduced for the long-run crowd-out effects. In the case of developed economies, over the study period, they have witnessed significant mergers and acquisitions    For developing economies in transition, the above and other reasons account for the long-run effects. First, developing and transition countries do engage in food manufacturing using domestic resources and investments. Attracting foreign investment presupposes local investments are inadequate based on the existing policy environment and conditions. Therefore, there will be a need for more attractive conditions to woo foreign investment. As a result, foreign investors tend to enjoy some benefits which may not be available to local investors.
Second, is the mode of entry; mergers and acquisitions. Through M&As, the original business ceases to exist. In cases where the previous shareholders do not re-invest in food manufacturing, this could result in a crowd-out of domestic investment. Third, foreign firms could import inputs from affiliate and non-affiliated companies abroad (Gallova, 2011). Such actions reduce market opportunities for host country firms. Not only do these firms fail to increase output and thereby re-invest, but also lose the market. This could result in complete shutdowns.
Fourth, is the macroeconomic dimension. Domestic currency can depreciate partly due to periodic profit transfers by MNEs and the opening of the financial markets. Local firms that do not export would have difficulty remaining in business as re-investments will become more expensive (Desai et al., 2004). The fifth is the weak investment regulation environment in some countries (Ufimtseva, 2020). Whilst these could lead to delays in translating FDI on the balance of payments into investments, the weak investment regulation environment could have other effects. Failure to ensure MNEs comply with domestic investment guidelines would lead to delay in realising the effects of FDI in the host economy; job creation that would lead to increases in income that would transmit to savings and consequently investments. MNEs could flout requirements for joint ownership arrangements.
Finally, lower managerial acumen, consequent lower performance of local firms than foreign firms, and failure of domestic firms to update technology could make it difficult for host country firms to become competitive hence, could be crowded out (Djokoto, 2013;UNCTAD, 2015). This reflects the competition effect (Markusen & Venables, 1999).
Combining all three development groups, the short-run effect coincides with those of developing and transition economies; no significant effect. The effects for the latter two certainly influenced the short-run effect for all three economy groups more than that of the former, developed economies. Statistical and economic and administrative reasons can be adduced to explain the overall short-run results. The standard errors of the long-run statistics are high relative to the coefficients for the short run, in some cases, covering the coefficients almost two times. This accounted for the insignificant effect of FDI on DI in the short run for developing economies in transition. From the economics and administrative perspective, resource acquisition in the host country could take some time to materialise just like regulatory and administrative processes. In the same vein, the setting up of processing facilities could last more than a year. Therefore, multinational enterprises may fail to transform all FDI into investment in the sense of the national account (Agosin & Machado, 2005). Thus, the economic effects of FDI on DI have a transmission trajectory that can only be transcended over lapsed time. In developing and transition economies where there could be significant regulatory and administrative inefficiencies, these time lags can be pronounced. In light of these, statistically significant short-run effects of FDI on DI are unlikely.
In the long run, one dollar increase in FDI into food manufacturing leads to 1.7731 dollars (more than one dollar) increase in DI. It is the crowd-in effect for the food manufacturing sector jointly. The long-run result agrees with the findings of Jude (2019) and Kejžar (2016) for transition economies, Pilbeam & Oboleviciute (2012) for EU12 and Wang (2010) for least developed countries. Although the long-run crowd-in effect is desirable, the result departs from the long-run crowd-out effect for each of the development groups. The departure, from the development groups, is rather interesting yet plausible. As the computation of the long-run effect is not an arithmetic average for which there should be a less than 1.00 value, but a statistical summation of the interaction of the coefficients with the standard errors (the Wald statistic), the more than 1.0 value is an acceptable outcome. Six out of the nine coefficients of FDI were positive. However, a closer examination revealed that the sizes of the positive coefficients were far larger than that of the negative coefficients. The DI coefficients were similar, two coefficients had negative signs but the other four had positive signs. Together, the size of the positive coefficients exceeds that of the negative coefficients. The effects of the DIs result in a small increase in the sum of the DI. Adding these to the coefficients of FDIs in Equation 10, produced a value greater than 1. The departure from the economic grouping results also confirms the approach of the paper to segregate the analysis into levels of development. Indeed, the total sample results would have masked the group results that would have led to a one-size-fits-all recommendation. Thus, different policy propositions will be required for the various development groups.

Novica Supic
Faculty of Economics, University of Novi Sad, Novi Sad, Serbia In general, the paper is well-written; however, there are some concerns that need to be addressed before accepting it for indexing. The presentation of relevant theories is overly extensive, as numerous theories are presented with minimal explanation of the mechanisms of FDI influence, which is the main focus of the work. As such, it is necessary to provide a more detailed presentation of the theories referenced by the author in the section where the obtained results are discussed.
Additionally, it is important to explain why variables with a time lag of t-2 are used as explanatory variables in the regression, alongside the time lag of t-1. What is the criterion for choosing a lag of t-2 instead of, for instance, a lag of t-3? The paper lacks unit root tests in panel models and tests for cross-section dependence.
Furthermore, the recommendations for public policymakers are overly general and do not clearly stem from the results of the econometric analysis or the theories presented.

If applicable, is the statistical analysis and its interpretation appropriate? Yes
Are all the source data underlying the results available to ensure full reproducibility?

Yes
Are the conclusions drawn adequately supported by the results? Yes I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard.

Version 2
Reviewer Report 24 June 2022 https://doi.org/10.5256/f1000research.55226.r85181 © 2022 Bekun F. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Festus Victor Bekun
Faculty of Economics Administrative and Social Sciences, Istanbul Gelisim University, Istanbul, Turkey The topic is interesting, and the author has done a great job in realizing the subject. However, there are few areas on the paper that is still lagging and should be addressed properly.

Introduction
The objective of the paper presented needs more clarifications to suit reader to understand the main idea of the paper especially for the study case is needed

Literature review
The literature is well written. However, there is need for more recent studies ranging from 2018-2022 to motivate the study properly. The entire study is too scanty and the related literature is not exhausted Revisiting the Nexus between FDI, financial development and economic growth: Empirical evidence from Nigeria. Journal of Public Affairs, e2561 1 . academics without compromising for study intent and quality.

Response
The equation 1 -10 are basic to the study. Equation 2 is the estimated model whilst equations 3-10 show how the effects are obtained. I have elected to keep them in their place.

Discussion
The discussion is well written, but the authors should link their findings to the previous studies in the literature.

Response
The findings are linked to previous research. The previous research is in coloured text in the discussion section.

Comment
There is a need for professional proofreading or consulting English native support ○

Response
This has been done.

Comment Conclusion
The sub-title should be conclusion and policy recommendation not only conclusion