Rural-Urban Linkages: Regional Financial Business Services’ Integration into Chilean Agri-Food Value Chains

Abstract

The spatial structure of urban-related industries and agri-food value chains is important for promoting sustainable linkages. Using an interregional input-output framework, this study explores the geography of inter-industry linkages between financial business services and the Chilean agri-food related industries from a subnational perspective. This framework allows adding evidence on rural-related economic activities and financial business services, covering Chilean internal geography, which has a regional concentration of both the business services supply and the agriculturally engaged regions, potentially blocking territorial competitiveness. Our findings indicate that the relationship between value-added and trade is consistent with the vertical fragmentation of domestic production associated with returns to scale. Consequently, while the value-added financial services are more intense in trade for global value chains, this occurs in regions specialized in agri-food industries and services. Our findings also show that Southern Chilean regions engaged in primary agricultural production have lower levels of financial services directly and indirectly embedded in both domestic and global value chains trade, thus highlighting an uneven geography of vertical integration within the country.

1. Introduction

Linkages between financial business services and agri-food industries have been considered to be a channel for efficient market integration, qualifying the allocation of resources through intermediation services and allowing value-adding into agri-food value chains (AVC) [1,2,3,4]. Despite the relevance of the financial sector for economic growth [5,6,7], the role of the input-output linkages network between financial business services and agri-food industries at the subnational level is understudied. Generally, vertical integration on the agri-food chain has a clear geographical component, whereas the interplay of financial services embedded in AVC trade is neglected from national-based studies [8,9,10,11], thus inhibiting the discussion on sustainable regional development.

Recent empirical advances, mainly in the input-output framework, has made it possible to track trade flows between vertically integrated production stages, allowing for a more detailed portrait of the intersectoral dependency among the agri-food chains [1,4,12,13]. Therefore, the efficient allocation of financial service resources can support the development of regional and sustainable agri-food value chains [14]. The vertical integration between both activities is likely to promote regional sustainable development from an interdisciplinary perspective [15]. Consequently, integration facilitates the allocation of funding resources to sustainable agricultural practices, thereby allowing promotion of environmental conservation, social equity, and economic viability, as proposed by the Sustainable Development Goals (SDGs) from the United Nations common agenda. Linking financial services and agri-food industries is a powerful enabler of sustainable development, could encourage the development of sustainable value chains, and fosters knowledge transfer and capacity building. Moreover, at the urban-rural level, integration plays a crucial role in facilitating the flow of capital from geographically specialized areas in primary sectors, thereby enabling upward movement along the sustainable agri-food value chain [16].

In this light, this study aims to measure the intersectoral integration of the financial business services’ value-added embedded in AVC trade from a multiscalar perspective, based on an interregional input-output application for Chile from 2008 to 2015. Our contribution is twofold. First, we offer spatial and temporal evidence, accounting for the trade in value-added (TiVA) related to the structural path of embedding urban-related financial business services into AVC’s trade. Second, we incorporate a multiscalar perspective, measuring the role of integration in domestic (between subnational regions) and global markets (from subnational regions to global markets), expanding the analytical input-output scope. The regional analysis of the agri-food value-added linkages provide a clear portrait of uneven geography for competitiveness in rural areas based on finance-related production integration.

We chose the Chilean case as the spatial component of AVC market integration is particularly relevant. The regions suitable for agri-food production are located in the southern areas, while the supply of financial business services is highly concentrated in the metropolitan region of Santiago. These regional inequalities may harm the innovation strategies and upgrading of the business model in rural territories since they are far from the large urban agglomerations within the country. Meanwhile, Chile has maintained its leadership as the largest exporter of agriculture-based sectors to GVC, providing an interesting study case for trade-based analyses [17,18]. In this regard, the opening of new markets and the expansion of traditional ones through free trade agreements have played fundamental roles in increasing Chilean integration into global markets [19]. Furthermore, although regional agri-food systems—including farmers and marketing networks—have been advanced to improve linkages within and among territories worldwide, interregional systems typically have lower vertical integration with financial-related activities [20,21].

A value chain approach is a key tool in analyzing economic transactions between regional systems. In this light, AVC covers all stages of the agri-food production process, from raw material to final demand, domestic or global, making the economic geography a relevant aspect for building development strategies among rural territories [22]. The AVC acts as an intermediary between agricultural producers and the growing economy, including financial service linkages generally located in large urban centers [23,24]. The mainstream literature on financial development has recently focused on highlighting the so-called finance-growth-nexus, pointing out the causality involving the qualification of the financial supply and the growth of the sectorial output [25,26,27,28,29,30,31]. However, empirically, little is studied about the spatial patterns of linkages between financial services and agriculture, capable of increasing the value-added embedded in trade.

To address these issues, we adopted an interregional and multisectoral input-output model for the Chilean economy, understanding the structural setting of the multiplier effects of production and trade and the mechanisms by which it is spatially transmitted within the economic system [4,32,33,34,35]. For that, we regionalized the national OECD input-output table series based on regional and industry-level data from the Central Bank of Chile. Thus, we extended the input-output framework, applying the hypothetical extraction method (HEM) to measure the bilateral trade in value-added (TiVA), accounting for domestic (DVC) and global value chains (GVC). Moreover, we measured the financial business services’ content through the final demand of selected agri-food sectors. In this regard, our results allow a better understanding of the regional nature of AVC and its potential linkages among regions along the value chain [35,36,37]. Within an IO framework, we consider the direct and indirect effects embedded in regional trade imbalances, tracking both agricultural and financial value-added spatially transmitted through trade flows.

This paper is structured into five sections, including this introduction. Section 2 details the regional disparities in Chile regarding finance and agricultural location assets, allowing us to build a clear picture of AVC and financial business services supply among the Chilean regions. Section 3 shows the methodological approach applied in our measurements, whereas Section 4 is an analysis of the main findings. Section 5 concludes and provides some policy considerations.

2. Dimensions of Regional Disparities in Finance and Agriculture

2.1. The Geography of Financial Business Services

The relevance in studying the geography of financial business services is pointed out by the growing interest in the financial growth nexus [25,26,27,28,29,30,31]. Although there is still debate about the exact causal direction of the link between finance and growth, a considerable amount of empirical evidence suggests that access to finance positively affects the performance of companies, increasing opportunities for economic growth [5,28,38]. Nevertheless, economics and business management studies often assume perfect capital mobility, implying assumptions of spatial homogeneity in access to finance [2,39]. Consequently, an understudied aspect is the geography of supply and access to financial services, as well as an assessment on how local economies can be affected by financing constraints [40,41,42].

Despite growing evidence of how financial constraints depend on the characteristics of companies–such as age, size, and economic sector—disregard for the spatial variation of financing generates a limited understanding of important vertical integration channels regarding companies’ linkages to business services [4,43]. Furthermore, the financial services supply concentration is not spatially blind, moving the capital to specific location hierarchies [2,23].

This is seen in Chile’s economic and spatial structure. Accordingly, Figure 1 shows the regional distribution of financial intermediation and insurance companies, revealing an apparent concentration around Santiago’s capital city, which is in the metropolitan region. Between 2008 and 2015, the number of companies in financial and insurance activities grew 40% in the metropolitan region of Santiago, concentrating 78% of all companies in this sector in the country, according to Servicios de Impuestos Internos (SII) data. Although other regions do not represent more than 5% of the total number of companies in the financial sector in the country, some interior regions showed considerable increases in total finance-related companies: Tarapacá and Antofagasta, 49%; Coquimbo and Valparaíso, 43% and 47%, respectively; O’Higgins, 52%; Bío-Bío and La Araucanía, 44%. Despite the clear increase, financial companies favor the economy of the areas around the capital city to the detriment of hinterland areas.

In the context of geographic fragmentation of production, the potential for vertical integration of different economic sectors with financial services is affected by the geographical distance of resource industries, which tend to be attracted to regions with intense availability of these natural resources [36,44,45]. The spatial concentration of financial markets implies that money tends to flow and accumulate in specific spatial areas, and are not evenly distributed in space [2,42], generating critical challenges to subnational companies accessing external financing sources. In addition, the role of urban agglomerations in providing better access to growth is a topic that has attracted considerable research and policy attention in recent years [46,47,48]. According to location theory, large cities create better opportunities for increasing returns by accumulating knowledge, the combination of labor, infrastructure, and inputs. Therefore, productivity gains tend to be greater in industrial and service sectors, including financial ones, at the expense of sectors located in areas far from urban centers, such as resource-based industries [39,49,50].

2.2. Agri-Food Value Chain and the Financial-Growth Nexus

The agri-food value chain (AVC) covers the entire range of activities and economic agents with forward and backward linkages that add value to goods and services, from production to final consumption [22,24]. The different value chains are comprised of varying levels in governance structure, and are fundamentally dependent on the business models they are based on, including drivers, processes, and resources throughout the chain [4,51]. Furthermore, the business model allows the company to organize production and reduce transaction costs by providing them with markets, technologies, inputs, credit, and extension services, as well as managing risks along the value chain [24,52,53].

Cross-country evidence has shown how funding constraints emerge as one of the most relevant factors that restrict business growth [38,54,55]. Thus, improving access to external sources of finance can be considered one of the main challenges for financing agri-food companies [29,56,57]. The value chain approach allows understanding financial linkages as an entry to reaching agri-food industries. It has been shown that one of the main gaps in financial systems is related to asymmetric information about potential borrowers, implying adverse selection and various moral risks [40,58,59,60]. In the context of value chains, economic entities tend to be better informed about linkages, allowing financial institutions both access to information and better conditions, in order to design financial products and services for different economic entities in the chain [61].

This integration of financial products and services is defined as the flow of funds to different links in the value chain in order to improve efficiency and competitiveness, reduce risk, and promote the upgrading of the value chain [2,62,63]. Accordingly, the rise of the AVC intensifies the need for investment through the financial services’ linkages. On the demand side, value chains optimize the use of infrastructure, labor, and financial capital to consolidate their market shares, meet consumer preferences, and reduce transaction costs for aggregating dispersed marketable surpluses [64,65,66]. However, if the focal place of financial linkages is in large cities, regions engaged in agriculture may have constraints on accessing the capital providers. Companies outside the networks may not be able to access the capital needed. Although there are theoretical reasons to postulate that business access to finance may be linked to the city’s size, one can also expect that the intensity and extent of this relationship will depend on the level of regional and sectoral development within a country [2,36]. The IO linkages offer conditions for incorporating financial services in the AVC’s output sector: this growth would occur through efficiency gains in financial transactions, which tend to contribute to promoting innovations, as well as reducing information costs, allowing the adoption of advanced technology and ensuring the efficient allocation of investment funds [38,53].

Unlike the spatial concentration of finance companies in the capital city, the agricultural companies are located in southern Chile. Figure 2 shows the regional location of these companies, revealing that between 2008 and 2015, about 57% of formal companies in agriculture-related activities are concentrated in the regions of O’Higgins, Del Maule, Del Biobío, and De La Araucanía. Some northern regions showed a decrease in the total number of agriculture companies, such as De Atacama and De Coquimbo, with −10% and −11%, respectively. Regarding financial linkages, the lack of geographic immateriality in the expansion of finance networks goes back to the need for external financing in backward-agriculture-engaged regions, consequently pointing to the relevance of finance in the architecture of spatial inequalities [42,63,67,68].

Empirical evidence has pointed to a negative relationship between the company’s geographical distance and location of financial services (e.g., local bank branches), and the adoption of innovations and upgrading at the firm level [68]. Ref. [69] suggests an increase in the cost of borrowing as the distance increases, while [55] found that innovative peripheral companies are more likely to have rejected funding requests. Distance directly influences courses and access to sources of finance in response to externalities agglomeration [2,70]. This financing bias for urban agglomerations is due to the proximity of issuers and investors, forming urban centers that act as focal points in developing functional financial markets [53,54,71,72]. Conversely, there is evidence on the positive impact of financing for economic growth, especially in regions with lower income and productivity levels [23,24,55]. External financing of AVC’s activities occurs through loans from commercial banks to contracted farmers or deposit receipts from recognized storage. In this regard, AVC financing is a particularly relevant aspect for the development of regions engaged in agri-food production [53,56,73,74].

3. Methodology

This study adopts a trade in value-added (TiVA) perspective to examine the interplay between financial business services and agri-food value chain (AVC) linkages within a multisectoral model. The methodology extends the global value chain (GVC) approach to an interregional system, as a novel regional setting for the Chilean case [16,75,76]. Furthermore, the utilization of TiVA measures highlights the allocation of intermediate inputs within regional production systems. Consequently, it can influence the production process beyond the trade in final goods, thus facilitating the development of linkages across the domestic (regional) and global supply chains. Additionally, this justifies the adoption of the input-output approach, as it enables the analysis of the economic structure among regions and industries [77,78].

In order to measure the financial business services’ value-added content embedded in agri-food-related value chains, let us first consider an interregional input-output model (IRIO) with $J$ industries (labeled as $i, j$), $R$ subnational regions ($r, s$), and $U$ final demand components for domestic ($U^r,U^s$) and foreign ($U^{RoW}$) consumption, as shown by Figure 3. The final structure given to the data provides a comprehensive and consistent record of the regional income accounting relationships between different sectors from 2008 to 2015. We selected this time period based on the availability of country-level matrices from the OECD and regional labor market data from the Servicio de Impuestos Internos (SII). The specifics regarding the regionalization of the matrices for the period 2008-2015 can be found in the Supplementary Material.

The model is grounded in the fundamental principle of general equilibrium, utilizing a social accounting matrix (SAM) to capture the interconnections within a regional economy, encompassing intermediate uses and final demand. In our context, the use of an Interregional Input-Output (IRIO) framework provides the advantage of linking consumption and interregional trade patterns to the inter-industry structure of intermediate demand at the subnational (internal) level. This modeling approach enables a comprehensive analysis of the vertical integration of value-added from the financial services sectors embedded within the final demand of the sectors that comprise the agri-food value chain.

Within an IO framework, the intermediate consumption from an industry $i$ to $j$, from region $R$ to $S$, is represented by ${\mathrm{z}}_{\mathrm{i}\mathrm{j}}^{\mathrm{R}\mathrm{S}}$; $\mathrm{A}$ is the technical coefficients’ matrix equal to the ratio between $z$ and the industrial output ${\mathrm{x}}_{\mathrm{j}}$, $\mathrm{A}=\mathrm{Z}{\left(\widehat{\mathrm{x}}\right)}^{-1}$. Therefore, the regional gross output can be expressed by the IRIO system as follows:

$$\mathrm{x}=\mathrm{Z}+\mathrm{F}i=\mathrm{A}\mathrm{x}+\mathrm{F}i$$

(1)

where $\mathrm{F}$ is the final demand, and $i$ is a summation vector of ones. This relationship can be expressed as:

$$\mathrm{x}={\left(\mathrm{I}-\mathrm{A}\right)}^{-1}\mathrm{F}i=\mathrm{L}\mathrm{F}i$$

(2)

where $\mathrm{L}={\left(\mathrm{I}-\mathrm{A}\right)}^{-1}$ is the Leontief matrix. The extended IRIO system allows us to analyze the specific regional and industry-related interdependencies: the gross output for two sectors (supposing label 1 refers to agriculture and label 2 to financial services business) in two regions (R and S) is given the relationship between the Leontief matrix and final demand:

$$\left[\begin{array}{c}{\mathrm{x}}_1^R\\ {\mathrm{x}}_2^R\\ {\mathrm{x}}_1^S\\ {\mathrm{x}}_2^S\end{array}\right]=\left[\underset{\mathrm{I}\mathrm{n}\mathrm{t}\mathrm{e}\mathrm{r}\mathrm{r}\mathrm{e}\mathrm{g}\mathrm{i}\mathrm{o}\mathrm{n}\mathrm{a}\mathrm{l} \mathrm{L}\mathrm{e}\mathrm{o}\mathrm{n}\mathrm{t}\mathrm{i}\mathrm{e}\mathrm{f}}{\underbrace{\begin{array}{cccc}{\mathrm{L}}_{11}^{RR}& {\mathrm{L}}_{12}^{RR}& {\mathrm{L}}_{11}^{RS}& {\mathrm{L}}_{12}^{RS}\\ {\mathrm{L}}_{21}^{RR}& {\mathrm{L}}_{22}^{RR}& {\mathrm{L}}_{21}^{RS}& {\mathrm{L}}_{22}^{RS}\\ {\mathrm{L}}_{11}^{SR}& {\mathrm{L}}_{12}^{SR}& {\mathrm{L}}_{21}^{SS}& {\mathrm{L}}_{22}^{SS}\\ {\mathrm{L}}_{21}^{SR}& {\mathrm{L}}_{22}^{SR}& {\mathrm{L}}_{22}^{SS}& {\mathrm{L}}_{22}^{SS}\end{array}}}\right]\left[\underset{\mathrm{F}\mathrm{i}\mathrm{n}\mathrm{a}\mathrm{l} \mathrm{d}\mathrm{e}\mathrm{m}\mathrm{a}\mathrm{n}\mathrm{d}}{\underbrace{\begin{array}{ccc}{\mathrm{f}}_1^{RR}& {\mathrm{f}}_1^{RS}& {\mathrm{f}}_1^{\mathrm{R},\mathrm{R}\mathrm{o}\mathrm{W}}\\ {\mathrm{f}}_2^{RR}& {\mathrm{f}}_2^{RS}& {\mathrm{f}}_2^{\mathrm{R},\mathrm{R}\mathrm{o}\mathrm{W}}\\ {\mathrm{f}}_1^{SR}& {\mathrm{f}}_1^{SS}& {\mathrm{f}}_1^{\mathrm{S},\mathrm{R}\mathrm{o}\mathrm{W}}\\ {\mathrm{f}}_2^{SR}& {\mathrm{f}}_2^{SS}& \underset{\mathrm{E}\mathrm{x}\mathrm{p}\mathrm{o}\mathrm{r}\mathrm{t}\mathrm{s}}{\underbrace{{\mathrm{f}}_2^{\mathrm{S},\mathrm{R}\mathrm{o}\mathrm{W}}}}\end{array}}}\right]i$$

(3)

One can account for the value-added from a whole industry. Specifically, the value-added generated by the financial services business services (sector 2) can be expressed as follows:

$${\mathrm{d}\mathrm{v}\mathrm{a}}_2^{\mathrm{R}}={\widehat{\mathrm{v}}}_2\mathrm{L}\mathrm{F}i$$

(4)

where ${\widehat{\mathrm{v}}}_2$ is a diagonal vector of value-added coefficients for region $R$ and industry $1$, with zeros elsewhere (${\widehat{\mathrm{v}}}_2=\left[\begin{array}{cccc}[v_2^R& 0& \dots & 0\end{array}\right]$). Equation (4) considers the total value-added for meeting the final demand; that is, the sum of all industries for both interregional and global demand. In addition, following [16], we can measure the interdependence between the value-added of a specific sector directly and indirectly embedded in the trade flows of another industry. Moreover, we also consider the trade flows for different geographical scales, accounting for them separately to integrate domestic value chains (DVC) and global value chains (GVC). We deal with that by treating both ${\mathrm{U}}^{\mathrm{R}\mathrm{S}}$ and ${\mathrm{U}}^{\mathrm{R},\mathrm{R}\mathrm{o}\mathrm{W}}$ components as separate from the $\mathrm{F}$ matrix.

Therefore, to account for the relationship between the value-added of one sector and the final demand for another, we extended the hypothetical extraction method (HEM) to measure the bilateral TiVA [76,79,80]. Importantly, this technique has three main advantages: (1) it allows measuring the effect of changes in the intermediate output within a Leontief structure; (2) it applies to the estimation of the effects of the counterfactual removals of a group of sectors; and (3) it extends to measure effects on trade in an IRIO system [81,82].

Thus, the amount of value-added from financial business services (sector 2) that is embedded in the value chain integration of agriculture (sector 1) from each subnational region $R$ can be expressed as the difference between the ${\mathrm{d}\mathrm{v}\mathrm{a}}_2^R$ (Equation (4)) and the hypothetical extraction counterfactual situation, where sector 2 of R (origin) does not trade with sector 1 of a region S (destination). Therefore, this counterfactual can be measured as follows:

$$\begin{gathered} {\overline{\mathrm{d}\mathrm{v}\mathrm{a}}}_{21}^{RS}={\widehat{\mathrm{v}}}_2^R{\left(\mathrm{I}-\overline{\mathrm{A}}\right)}^{-1}\overline{\mathrm{f}}i \\ {\overline{\mathrm{d}\mathrm{v}\mathrm{a}}}_{21}^{RS}=\left[\begin{array}{cccc}0& 0& 0& 0\\ 0& {\mathrm{v}}_2^{\mathrm{R}}& 0& 0\\ 0& 0& 0& 0\\ 0& 0& 0& 0\end{array}\right]\left[\begin{array}{cccc}{\mathrm{L}}_{11}^{RR}& {\mathrm{L}}_{12}^{RR}& {\mathrm{L}}_{11}^{RS}& {\mathrm{L}}_{12}^{RS}\\ {\mathrm{L}}_{21}^{RR}& {\mathrm{L}}_{22}^{RR}& 0& {\mathrm{L}}_{22}^{RS}\\ {\mathrm{L}}_{11}^{SR}& {\mathrm{L}}_{12}^{SR}& {\mathrm{L}}_{21}^{SR}& {\mathrm{L}}_{22}^{SS}\\ {\mathrm{L}}_{21}^{SR}& {\mathrm{L}}_{22}^{SR}& {\mathrm{L}}_{22}^{SS}& {\mathrm{L}}_{22}^{SS}\end{array}\right]\left[\begin{array}{cc}{\mathrm{f}}_1^{RR}& 0\\ {\mathrm{f}}_2^{RR}& {\mathrm{f}}_1^{RS}\\ {\mathrm{f}}_1^{SR}& {\mathrm{f}}_1^{SS}\\ {\mathrm{f}}_2^{SR}& {\mathrm{f}}_2^{SS}\end{array}\right]i \end{gathered}$$

(5)

The HEM strategy shows us that the value chain integration measure is the difference between the actual domestic value-added (DVA) and the hypothetical counterfactual situation. In this regard, the bilateral TiVA from sector 1 in R that is traded to sector 2 of S can be expressed as follows:

$${\mathrm{d}\mathrm{v}\mathrm{a}}_{21}^{\mathrm{R}\mathrm{S}}={\mathrm{d}\mathrm{v}\mathrm{a}}_2^R-{\overline{\mathrm{d}\mathrm{v}\mathrm{a}}}_{21}^{\mathrm{R}\mathrm{S}}$$

(6)

For GVC trade analysis, we extended the HEM technique applied to an IRIO system, considering that domestic production can provide for the final demand of exports [83]. In this case, the value-added from sector 2 in region R that is embedded in the exports of sector 1 is given by:

$${\mathrm{d}\mathrm{v}\mathrm{a}}_{21}^{\mathrm{R},\mathrm{R}\mathrm{o}\mathrm{W}}={\mathrm{d}\mathrm{v}\mathrm{a}}_2^R-{\widehat{\mathrm{v}}}_2^R\mathrm{L}\left[\begin{array}{c}0\\ {\mathrm{f}}_2^{1,\mathrm{R}\mathrm{o}\mathrm{W}}\\ {\mathrm{f}}_1^{2,\mathrm{R}\mathrm{o}\mathrm{W}}\\ {\mathrm{f}}_2^{2,\mathrm{R}\mathrm{o}\mathrm{W}}\end{array}\right]i$$

(7)

We incorporate each region’s gross imports and sector in the IRIO system to complete the trade cycle. We assume that imports generate regional value-added with the local Leontief production technology as if they were produced inside the country [83]. This allows us to incorporate foreign markets from the perspective of purchases and sales of TiVA, accounting for the DVA embodied towards GVC.

Data

We have estimated an interregional input-output (IRIO) table series for Chile from 2008 to 2015. The matrices were regionalized into a typical structure from the national OECD tables, using regional and sectoral level data provided by the Central Bank of Chile. Appendix I show the details of the regionalization approach used [84]. The IRIO tables have 36 industries and cover 15 Chilean regions.

Table 1. Regional Gross Product (by Chilean Regions).

	2008	Share (%)	2010	Share (%)	2012	Share (%)	2015	Share (%)	Average Annual Variation
R1	722	0.8%	795	0.8%	928	0.8%	1209	0.8%	7.7%
R2	2762	3.2%	3520	3.4%	2873	2.4%	3355	2.3%	3.4%
R3	10,558	12.3%	13,939	13.6%	14,169	11.9%	14,553	10%	5.2%
R4	2207	2.6%	3065	3%	3567	3%	3191	2.2%	6.3%
R5	2650	3.1%	3558	3.5%	4049	3.4%	4247	2.9%	7.6%
R6	7388	8.6%	9162	8.9%	10,553	8.9%	13,418	9.2%	8.9%
R7	37,426	43.6%	43,462	42.4%	53,525	45.1%	67,439	46.3%	8.8%
R8	4286	5%	5399	5.3%	5889	5%	7282	5%	8%
R9	3257	3.8%	3374	3.3%	4091	3.4%	5454	3.7%	7.8%
R10	7178	8.4%	7737	7.5%	9270	7.8%	12,164	8.4%	7.9%
R11	2287	2.7%	2683	2.6%	3064	2.6%	4005	2.8%	8.4%
R12	1172	1.4%	1399	1.4%	1587	1.3%	2135	1.5%	9%
R13	2459	2.9%	2804	2.7%	3299	2.8%	4811	3.3%	10.3%
R14	452	0.5%	567	0.6%	607	0.5%	751	0.5%	8.3%
R15	1001	1.2%	1148	1.1%	1324	1.1%	1550	1.1%	0%
Total	85,805	100%	102,612	100%	118,795	100%	145,564	100%	7.2%

Note: R1—De Arica y Parinacota, R2—De Tarapacá, R3—De Antofagasta, R4—De Atacama, R5—De Coquimbo, R6—De Valparaíso, R7—Región Metropolitana de Santiago, R8—Del Libertador General Bernardo O’Higgins, R9—Del Maule, R10—Del Biobío, R11—De La Araucanía, R12—De Los Ríos, R13—De Los Lagos, R14—Aysén del General Carlos Ibáñez del Campo, R15—De Magallanes y de la Antártica Chilena.

summarizes the gross regional product for each Chilean region from the database we used.

Specifically, we are interested in the relationship between the financial business services sectors and the agriculture-related sectors. We focused on the relationship between the sectoral value-added and the final demand (as well as in a sectoral perspective) by breaking down the interindustry and interregional relationships for five specific sectoral groups [36], as shown in

Table 2. Sectorial groups focused on in the analysis (agri-food and business services).

Industry		OECD Industries	Outflow Type
1	Agriculture	TTL_01T03: Agriculture, forestry, and fishing	Goods
2	Food related industry	TTL_10T12: Food products, beverages, and tobacco	Goods
3	Food services	TTL_55T56: Accommodation and food services	Services
4	Financial Business Services	TTL_62T63: IT and other information services	Services
		TTL_64T66: Financial and insurance activities
		TTL_68: Real estate activities
		TTL_69T82: Other business sector services

. The sectoral classification relates to a commonly used process in input-output studies for sectoral harmonization. The idea is to summarize the information through sectoral aggregation strategies. To achieve this, we aligned the sectoral information from the Servicio de Impuestos Internos of Chile and the OECD input-output tables. Both databases are compatible through standardized sectoral classifications, such as ISIC Rev. 4. It is important to highlight that—to avoid the problem of aggregation—we use the sum of regional and sectoral results.

4. Results

This section is divided into three parts. First, we examine the regional composition of trade in value-added (TiVA) for both DVC and GVC for all sectors to build a picture regarding the market integration profile of the Chilean economy. Second, we analyze the TiVA results of the AVC sectors to identify the location preference patterns of the origin of the value-added embedded in the agri-food sectors. Third, we explore the interplay between the value-added from financial business services embedded in AVC trade for both DVC and GVC.

4.1. TiVA to DVC and GVC

Table 3. Total domestic value-added embedded in both DVC and GVC (outflows), by Chilean region (millions of current dollars prices).

Region	2008		2009		2010		2011		2012		2013		2014		2015
	DVC	GVC	DVC	GVC	DVC	GVC	DVC	GVC	DVC	GVC	DVC	GVC	DVC	GVC	DVC	GVC
R1	548	260	587	204	683	216	794	271	875	243	981	265	993	238	908	224
R2	739	2845	733	2799	1071	3857	1136	3683	1107	2420	1163	2808	1056	2853	986	2111
R3	1136	14,125	999	13,370	1901	19,296	2098	19,737	1862	19,471	1584	17,426	1593	16,624	1395	1367
R4	863	2299	919	1989	1368	3088	1476	3824	1336	3198	1417	3125	1339	2615	1303	1882
R5	939	1986	922	1757	1193	3160	1328	4144	1369	3777	1441	3232	1454	2938	1370	2187
R6	824	4252	1094	3888	1722	4942	1879	5959	1944	5961	2386	5854	2037	5549	2106	4794
R7	9005	14,396	9395	12,719	1168	15,690	14,133	18,464	16,839	18,867	18,429	19,586	17,600	18,434	16,253	15,872
R8	1259	3398	1102	3350	1453	4490	1608	4892	1533	4706	1662	4507	1823	4483	1712	3857
R9	1619	1307	1486	1055	1476	1168	1734	1388	1799	1337	1932	1349	2028	1350	1925	1453
R10	1541	3294	1635	2693	1539	2897	1774	3582	2274	3276	2534	3377	2433	3592	2328	3322
R11	788	854	841	674	967	810	1203	906	1464	831	1600	865	1541	817	1475	794
R12	617	541	651	436	766	541	870	593	988	551	1093	589	1091	591	1057	552
R13	824	1017	857	944	1097	1008	1242	1277	1388	1165	1562	1391	1592	1734	1385	1337
R14	438	128	459	128	581	152	675	197	696	184	837	240	920	285	703	136
R15	518	589	541	460	653	547	751	625	879	568	1018	584	989	607	926	359
Chile	21,658	51,291	22,223	46,466	27,541	61,863	32,702	69,542	36,354	66,555	39,641	65,198	38,487	62,713	35,833	51,947
National composition	30%	70%	32%	68%	31%	69%	32%	68%	35%	65%	38%	62%	38%	62%	41%	59%

Note: R1—De Arica y Parinacota, R2—De Tarapacá, R3—De Antofagasta, R4—De Atacama, R5—De Coquimbo, R6—De Valparaíso, R7—Región Metropolitana de Santiago, R8—Del Libertador General Bernardo O’Higgins, R9—Del Maule, R10—Del Biobío, R11—De La Araucanía, R12—De Los Ríos, R13—De Los Lagos, R14—Aysén del General Carlos Ibáñez del Campo, R15—De Magallanes y de la Antártica Chilena.

shows the total TiVA originating in each Chilean region between 2008 and 2015. The regional value-added embedded for international trade exceeds the inter-regional trade, pointing to the export-based orientation of the national economy. On average, 63% of the regional TiVA supplies the GVC. Comparing the regional participation of the value-added for DVC and GVC, it is also noted that the contributions to the global markets are heterogeneous among the Chilean regions. There is an apparent prominence of the Region of Antofagasta, which incorporates around 90% of the local value-added for GVC with specialization in the supply of mining extractive industries. In this regard, It is relevant to point out that the value-added consumed at the intraregional level is not computed for only the interregional and global flows. Following that are the Regions of Valparaíso and Del Libertador General Bernardo O’Higgins, both at about 69% of the domestic value-added embedded into the GVCs—most of this amount relates to the agricultural industries. The regions of Tarapacá and Coquimbo subsequently appear with 68% and 61%, respectively, towards GVC.

Despite the regional composition in the provision for DVC and GVC, there is a considerable concentration of total value-added in the metropolitan region of Santiago, given its economic and population representativeness in the country. In 2015, 37% of all value-added sold in Chile originated in Santiago’s capital city region. Despite the economic concentration, the composition of DVC and GVC is relatively balanced in the Metropolitan Region of Santiago, having average shares between 2008 and 2015 at around 51% and 49%, respectively. Furthermore, the national capital region centralizes the supply of goods and services to the whole country due to the industrial complex and the presence of a central government structure—providing public services to the Chilean hinterland. In addition, the productive concentration responds to the agglomeration returns associated with Santiago’s service and manufacturing sectors. Consequently, while the value-added financial services are more intense in trade for global value chains, this occurs in regions specializing in agri-food industries and services.

We can identify regional patterns of integration with DVC and GVC by analyzing the net balance sheets of TiVA outflows and inflows. Figure 4 details the evolution between 2008 and 2015 of the difference between the total value-added outflows and inflows for DVC (part a) and GVC (part b). The metropolitan region of Santiago coordinates interregional value-added flows, in which all other regions are net importers in DVCs. Concerning the GVC integration, although our TiVA measure assumes Leontief’s technology at the regional level, the value-added in exports exceed the total value-added imported for all regions throughout the analysis period. The largest net value-added exporter, with high forward linkages for GVC, is the region of Antofagasta. Subsequently, the metropolitan region of Santiago, the region of Libertador O’Higgins, and the Valparaíso are also net importers but have more diversified production structures.

The geographic structure of production indicates the abundance of supply and demand regarding manufacturing and service activities in the metropolitan region of Santiago, revealing a governance role in coordinating interregional value-added flows. In this light, smaller regional economies are also characterized by a more significant relative share of value-added in exports, potentially depending on local endowments and the geographic distribution of natural resources and local characteristics, such as productivity and capital or labor-intense uses. Furthermore, the spatial distribution of value-added in trade reveals constraints on the local content implicitly embedded in DVC and GVC, potentially imposing limits on regional development. The following section provides a clearer picture of these regional aspects focusing on AVC.

4.2. TiVA for Agri-Food-Related Industries

The charts of Figure 5 show the results of TiVA measures regarding the AVC sectors in 2015: agriculture, food-related industries, and food services. It is clear that the southern regions are responsible for most of the value-added embedded in the AVC trade flows, highlighted by the regions of O’Higgins, Maule, Bio-Bio, and La Araucanía. Among these regions, the agro-export orientation is evident in Bio-Bio, Maule, and O’Higgins.

There is a straightforward relocation of the food-related industries and food services, compared to the primary activity of agriculture. The metropolitan region of Santiago stands out in the supply of the agri-food industry to GVC, allocating around 88% of the regional value-added to foreign demand. Santiago’s region accounts for 40% of all value-added traded to the rest of the world at the national level. Despite the lower economic representativeness of food services, it is interesting to note that 66% of all value-added embedded in trade, regardless of whether it is for DVC or GVC, originates in the RMS. This result reinforces the centrality of RMS in coordinating the value-added interregional flows in the architecture of domestic vertical integration. Despite having a low share of agricultural value-added (primary sector), the Chilean capital city specializes in more advanced stages along the production chain, increasing more value for trade.

Given the economic essentiality of food production, the results show that the domestic market is essential for Chilean AVC, as indicated by the results of interregional net balances in 2008 and 2015, shown in

Table 4. Interregional net balances for domestic AVC (2008 and 2015).

Region	2008			2015
	AGR	FOO	FOS	AGR	FOO	FOS
R1	2.85	−1.85	−2.30	24.56	−11.39	−6.57
R2	−21.24	−14.71	−3.14	−19.39	−25.18	−8.25
R3	−81.86	−53.54	−31.12	−98.86	−108.22	−75.40
R4	3.80	−10.41	−7.19	2.20	−18.60	−14.97
R5	75.74	−13.40	−6.09	131.15	−26.01	−14.54
R6	−105.30	−41.02	−24.41	−89.21	14.83	−31.93
R7	−164.25	30.04	129.43	−316.17	42.88	273.23
R8	151.48	16.13	−7.39	278.06	8.57	−26.18
R9	71.21	24.58	−4.86	133.38	23.16	−13.95
R10	−28.74	48.77	−17.52	−67.84	68.88	−34.25
R11	64.46	1.00	−6.46	63.57	−2.99	−9.98
R12	−14.48	10.02	−4.41	−12.24	13.19	−8.85
R13	27.15	7.66	−7.12	−25.64	28.76	−18.16
R14	41.34	−7.94	−3.17	28.91	−9.73	−4.78
R15	−22.16	4.67	−4.25	−32.48	1.85	−5.41

Note: R1—De Arica y Parinacota, R2—De Tarapacá, R3—De Antofagasta, R4—De Atacama, R5—De Coquimbo, R6—De Valparaíso, R7—Región Metropolitana de Santiago, R8—Del Libertador General Bernardo O’Higgins, R9—Del Maule, R10—Del Biobío, R11—De La Araucanía, R12—De Los Ríos, R13—De Los Lagos, R14—Aysén del General Carlos Ibáñez del Campo, R15—De Magallanes y de la Antártica Chilena. Industrial groups: AGR—Agriculture; FOO—Food-related industries; FOS—Food services. Legend: The shades of red represent the lowest relative values, indicating a net import of value added. The shades of blue indicate positive net flows with regions having a net export of value added.

. Regional patterns of local content embedded in trade suggest a clear geographic structure of interregional transfers in Chilean agri-food chaining. First, the northern Chilean regions (e.g., Tarapacá and Antofagasta) increased their positions as net importers of value-added in the three sectors of AVC between 2008 and 2015. Second, it is found that the main source of goods in the agricultural sector is located in the southern regions of O’Higgins, Maule, La Araucanía, Coquimbo, and Los Lagos. Furthermore, it is interesting to note that the main domestic consumer market of these goods is concentrated in the metropolitan region of Santiago, De Valparaíso, and De Antofagasta. Although our indicators do not consider the regional populational size, the results point to a spatial differentiation in the endowment of factors required by AVC production. The AVC’s integration profile in the Region of Bío-Bío, which allocates much of the domestic value-added towards GVC, is noteworthy because it seems to have less relative economic prominence in terms of the provision of agricultural goods for DVC. This fact is evident if one compares it with the neighboring regions engaged in agricultural exploration. The region of O’Higgins dominates the value-added provision for the agriculture and food-industries sectors to meet domestic interregional demand, while the RMS stands out in the food-services sector.

In an economy with regional interdependencies, differences in local autarch prices generate competitive advantages in the primary sector for regions engaged in the agricultural chain and a relative abundance of factors. In this sense, as agricultural production factors have restricted mobility, production tends to specialize in specific regions among the economic geography: This is the case of the AVC in interregional trade for some southern Chilean regions, which have an essential consumer market in the northern areas of the country. We also draw attention to the difference in value-added sold internally for the sectors of food-related industries and food services, which move to the most densely urbanized regions—mainly surrounding the Santiago capital city.

These results point out relevant aspects about the structure of Chilean agri-food production in regional terms. However, they do not provide elements related to vertical integration with other sectors of the internal economic structure. Given the internally heterogeneous reliance on natural resources, southern Chilean regions often have less diversified economic bases and a greater dependency on international commodity prices. In this regard, the vertical integration at the subnational level may offer better opportunities to local resource-rich communities for capturing value-added, and internalizing the benefits to intersectoral linkages. Furthermore, the following section explores the vertical linkages between the financial business services’ value-added embedded in the agri-food sectors’ trade.

4.3. Financial Business Services into Agri-Food Trade

This section analyzes the financial business services’ value-added in trade for agri-food value chains.

Table 5. Financial business services embedded in agriculture-related industries for DVC and GVC.

Agriculture
Region	DVC					GVC					Variation on Composition
	2008	(%)	2015	(%)	Relative Variation	2008	(%)	2015	(%)	Relative Variation	DVC	GVC
R1	1.7	3%	2.3	3%	−12%	0.7	1%	0.8	1%	−42%	6%	−17%
R2	1.1	2%	1.4	2%	−13%	0.0	0%	0.0	0%	−45%	0%	−31%
R3	1.4	3%	1.0	1%	−51%	0.0	0%	0.0	0%	−73%	0%	−49%
R4	2.1	4%	2.7	3%	−15%	0.6	1%	1.2	1%	13%	−13%	29%
R5	4.7	9%	7.3	9%	4%	2.7	4%	4.5	4%	−9%	−2%	3%
R6	0.4	1%	2.1	3%	203%	3.2	5%	12.8	11%	119%	12%	−2%
R7	0.9	2%	0.6	1%	−53%	9.3	15%	22.8	20%	35%	−224%	6%
R8	14.3	27%	20.6	25%	−5%	12.0	19%	19.8	17%	−10%	−6%	7%
R9	6.3	12%	11.7	14%	22%	6.2	10%	11.4	10%	0%	0%	−1%
R10	4.9	9%	7.4	9%	−1%	13.0	21%	19.6	17%	−17%	0%	0%
R11	5.0	9%	7.3	9%	−4%	5.4	9%	6.4	6%	−35%	10%	−11%
R12	2.5	5%	4.6	6%	22%	2.1	3%	3.5	3%	−10%	5%	−7%
R13	5.5	10%	7.7	10%	−7%	6.5	10%	10.2	9%	−14%	−6%	5%
R14	1.8	3%	2.9	4%	2%	0.6	1%	0.8	1%	−28%	4%	−14%
R15	0.8	1%	1.4	2%	13%	0.1	0%	0.3	0%	58%	−8%	35%
Chile	53.4	100%	81.1	100%		62.5	100%	114.0	100%		−11%	8%
Food−Related Industries
Region	DVC					GVC					Variation on Composition
	2008	(%)	2015	(%)	Relative Variation	2008	(%)	2015	(%)	Relative Variation	DVC	GVC
R1	1.5	1.5%	1.1	0.8%	−44.3%	0.8	0.2%	0.1	0.0%	−84.1%	27.5%	−245.2%
R2	2.2	2.3%	2.3	1.8%	−21.3%	3.1	0.6%	1.4	0.3%	−54.1%	33.6%	−55.1%
R3	2.1	2.1%	1.3	1.0%	−52.4%	10.1	2.1%	3.9	0.8%	−60.9%	33.0%	−11.1%
R4	2.3	2.4%	2.4	1.8%	−22.1%	0.1	0.0%	0.1	0.0%	−1.0%	0.3%	−6.8%
R5	1.6	1.7%	1.7	1.3%	−19.9%	0.4	0.1%	0.2	0.0%	−44.9%	10.5%	−77.4%
R6	4.8	5.0%	14.1	10.8%	118.5%	31.1	6.4%	40.5	8.5%	33.2%	47.8%	−16.6%
R7	36.5	37.5%	49.3	38.0%	1.2%	368.2	75.4%	343.6	71.9%	−4.6%	28.0%	−4.0%
R8	4.9	5.1%	4.5	3.5%	−30.9%	8.2	1.7%	8.2	1.7%	1.4%	−4.8%	2.7%
R9	5.3	5.4%	5.6	4.3%	−19.9%	6.9	1.4%	7.2	1.5%	5.5%	1.9%	−1.5%
R10	17.4	17.9%	22.1	17.0%	−5.0%	38.0	7.8%	46.7	9.8%	25.6%	2.0%	−0.9%
R11	2.4	2.5%	2.8	2.2%	−14.0%	3.6	0.7%	3.6	0.8%	2.0%	7.7%	−6.0%
R12	4.8	5.0%	5.3	4.0%	−18.6%	4.3	0.9%	4.0	0.8%	−4.1%	6.4%	−8.3%
R13	4.9	5.1%	11.2	8.6%	70.7%	6.7	1.4%	14.5	3.0%	123.2%	2.3%	−1.8%
R14	0.8	0.8%	1.2	0.9%	16.4%	0.1	0.0%	0.1	0.0%	48.4%	0.4%	−6.4%
R15	5.7	5.9%	4.9	3.8%	−35.5%	6.4	1.3%	3.4	0.7%	−44.8%	19.6%	−28.1%
Chile	97.4	100.0%	129.8	100.0%		488.0	100.0%	477.6	100.0%		22.2%	−6.0%
Food−Services
Region	DVC					GVC					Variation on Composition
	2008	(%)	2015	(%)	Relative Variation	2008	(%)	2015	(%)	Relative Variation	DVC	GVC
R1	0.7	0.8%	0.8	0.5%	−32.5%	0.1	0.1%	0.0	0.0%	−62.1%	5.0%	−163.3%
R2	1.6	1.8%	2.2	1.4%	−20.2%	0.8	1.2%	0.6	0.9%	−27.5%	13.2%	−48.8%
R3	1.0	1.1%	0.8	0.5%	−51.6%	0.3	0.4%	0.3	0.4%	−11.9%	−3.6%	11.4%
R4	1.6	1.7%	1.8	1.2%	−30.6%	0.1	0.2%	0.1	0.1%	−26.4%	2.0%	−43.9%
R5	1.3	1.4%	1.6	1.0%	−25.9%	0.4	0.6%	0.3	0.5%	−22.4%	7.9%	−37.1%
R6	0.5	0.6%	1.3	0.9%	58.9%	0.8	1.2%	1.1	1.6%	32.8%	27.9%	−34.3%
R7	77.6	85.7%	133.4	88.0%	2.7%	58.2	92.8%	62.7	92.9%	0.2%	16.0%	−34.1%
R8	1.5	1.7%	1.5	1.0%	−40.9%	0.6	1.0%	0.5	0.8%	−21.7%	4.4%	−12.5%
R9	0.8	0.9%	1.2	0.8%	−10.7%	0.2	0.3%	0.3	0.4%	34.3%	0.7%	−2.8%
R10	0.6	0.6%	1.1	0.7%	12.5%	0.6	1.0%	0.7	1.1%	11.3%	18.9%	−27.7%
R11	0.7	0.8%	1.4	0.9%	15.4%	0.3	0.4%	0.3	0.5%	13.4%	9.9%	−42.8%
R12	0.6	0.6%	1.0	0.6%	−0.9%	0.1	0.1%	0.1	0.1%	−10.5%	4.8%	−64.2%
R13	0.8	0.9%	1.2	0.8%	−8.4%	0.3	0.5%	0.3	0.5%	1.7%	7.7%	−29.5%
R14	0.5	0.5%	0.8	0.6%	6.2%	0.0	0.0%	0.0	0.0%	−10.0%	1.0%	−82.0%
R15	0.8	0.9%	1.4	0.9%	5.7%	0.1	0.1%	0.1	0.1%	22.2%	2.1%	−32.0%
Chile	90.5	100.0%	151.6	100.0%		62.7	100.0%	67.5	100.0%		14.7%	−32.9%

Note: R1—De Arica y Parinacota, R2—De Tarapacá, R3—De Antofagasta, R4—De Atacama, R5—De Coquimbo, R6—De Valparaíso, R7—Región Metropolitana de Santiago, R8—Del Libertador General Bernardo O’Higgins, R9—Del Maule, R10—Del Biobío, R11—De La Araucanía, R12—De Los Ríos, R13—De Los Lagos, R14—Aysén del General Carlos Ibáñez del Campo, R15—De Magallanes y de la Antártica Chilena.

computes the vertical integration measures of the intersectoral in all three agriculture-related sectors considered in our analysis at the regional level for 2008 and 2015. The results indicate the interindustry composition of the value-added content traded by agriculture (part a), food-related industries (part b), and food services (part c).

The value-added contribution of financial business services is evident for agriculture trade originating in the region of O’Higgins, as it serves both DVC and GVC. Between 2008 and 2015, the sophistication of value-added has increased further to meet the requirements of exports’ demand. In the regions of Bío-Bio, the metropolitan region of Santiago, and Valparaíso, it is noteworthy that the agricultural trade for GVC is more intense in its vertical integration with financial services’ embedded content compared to the domestic destinations. These results reflect the fundamental role of the value-added financial services in qualifying trade to GVC, given the direct and indirect contributions to Chilean agricultural production. However, it is straightforward that the quality of linkages with financial services moves across economic geography for both regionally and market-oriented perspectives: regions engaged in primary production are less integrated with financial services than regions positioned in forwarding AVC stages.

Despite the economic importance of agriculture in some southern regional clusters, the forward production sectors within AVC, such as food-related industries and food services, are more closely linked with financial services in the metropolitan region of Santiago and Bio-Bio for both DVC and GVC. There is evidence that as the agri-food chain stages advance, vertical integration with the financial business sectors increases considerably. In regional terms, it can be noted that in the central regions of Chilean geography, such as Bio-Bio (with greater importance for the agri-food industry), or the surroundings of Santiago (with a relevant presence of food services), the use of financial services’ intermediary is more significant when compared to the economic structures of the southern regions. The requirements for intermediate use of the integration with the financial business services are heterogeneous for both regional and industrial terms.

An implication of the increase in the importance of services in exports is revealed in the exposure of national economies to international trade, although the verticalization of financial services seems to point to a spatial concentration of tradable services, revealing relevant location disadvantages in the Chilean agricultural economy [16,85]. The central role of large cities in the provision of financial services seems to provide uneven opportunities of financial linkages in southern agriculture compared to companies of tradable financial service supplies located nearby, as found by [2].

The decoupled regional patterns of financial services can be further revealed when comparing the potential intermediate use of financial activities in regional production in the different sectors of the agri-food value chain, as discussed by [86]. The traded goods have qualifications in terms of embedded financial business content among the regions engaged in primary production, such as Los Ríos and La Araucanía, the agri-food industry located in Bío-Bío, Del Maule, and the Metropolitan Region of Santiago. Furthermore, the market orientation is clear: exports of agricultural goods, the food-industries, and food services are more intense in value-added financial services than the trade that supplies the subnational interregional markets.

5. Conclusions

In this study, we adopted a regional perspective (within the country) in order to measure the relative importance of financial business services’ value-added, directly and indirectly embedded in agri-food production and trade considering different geographical scales, accounting for both domestic and global trade flow levels. In Chile, the interregional value chains based on natural resource-rich subnational areas reinforce regional inequalities regarding the embeddedness of financial business services in both production and trade.

While natural resources’ geography may act as a driver to reduce regional inequality, interregional and intersectoral linkages are likely to lead in the opposite direction, mainly in business services content in trade. It was noted that the regional participation in value chains is differentiated by the degree of penetration of local content coupled with trade flows. Accordingly, the degree of local assets incorporated into AVC is essential for the southern regions, as the functional spatial divisions across the value chain depend on the location preferences. Despite the benefits of IO linkages spread across subnational regions, the engaged agricultural areas appear to have less potential to improve their vertical linkages to services business sectors.

In this regard, our findings show that the indirect effects of the intermediary use of the financial services sectors’ value-added on the agri-food industry are more remarkable regarding the GVC and even more intense for the food-related industries. In summary, there appears to be spatial segmentation of intermediary financial services supporting the activities of sectors directly linked to agriculture. The productive linkages of tasks associated with financial activities point to uneven internal geography: on the one hand, financial business services provide inputs to domestic agricultural trade, and on the other hand, financial services are embedded in food industry and food services for attending the GVC. Regionally, the geography of Chilean trade and interindustry integration indicates better opportunities for quality linkage agriculture activities in Bio-Bio, Los Lagos, and the metropolitan region. Valparaíso demonstrates that having more complex and interconnected production networks favors the local business environment and the sophistication of the tradable value-added.

Moreover, the vertical integration between rural-related industries—such as agriculture—and urban-related financial sectors is a powerful enabler of sustainable development. It harnesses financial resources to support sustainable agricultural practices, encourages the development of sustainable value chains, and facilitates knowledge transfer and capacity building. The results suggest the existence of a central economic space that provides financial services to sectors located in less economically developed areas, which may restrict the potential for sustained regional development. The coordination between territories is a fundamental element for ensuring the regional capacity to generate and convert value into territorial development.

These results suggest the relevance of promoting improvements for creating value-added agricultural support services in the main natural resource exploitation regions, and also for northern Chile specialized in mining industries. Furthermore, it has been shown that exports of agricultural goods, food industries, and food services are unevenly distributed among Chilean regions due to the disparity between local supply and demand, imposing the need for regional strategies that favor the qualification of intersectoral and interregional linkages. In addition, policymakers could improve the long-term learning process significantly to facilitate regional development. In order to increase agri-food competitiveness at the regional level, Chile still requires well-designed policies and the capacity to promote vertical service integration. In agriculture-based regions, the improvement of productivity and creation of value-added may need to disperse the IO linkage networks in some business services, allowing diversification of local economic bases and further quality content bundled into agricultural outcomes.

Theoretically, the presented results allow for the association of agglomeration economies’ effects with the location of agricultural and service activities, reinforcing the rural-urban duality. Services are attracted to economies of scale, leading to a geographical concentration of services, mainly in large urban areas. Agricultural activity, on the other hand, tends to move towards rural areas due to the availability of natural resources. However, these opposing forces of location impact the ability of agri-food industries to add value through access to financing from a spatial perspective. The economic costs of distance tend to negatively affect the potential to add value to production in the agri-food chain. The results of this study support the discussion on rural-urban disparities. From a productive and managerial perspective, the analysis of linkages is important for understanding the resources required by agri-food industries to generate their production and final value. It is considered relevant to comprehend the linkages with the service sectors, which have the potential to enhance production value [87].

The spatial results suggest that rural areas with a higher contribution from agri-food industries incorporate value from business service sectors generated in urban areas, particularly in the metropolitan region. One of the main limitations of this approach is the inability to capture variations at the municipal level, which could also reflect a center-periphery model favoring value generation in sub-regional metropolitan areas, such as capitals. However, given the existing subnational disparities in Chile, it was possible to observe the concentration of business activity in the metropolitan region compared to other subnational areas. The input-output analysis has certain limitations that should be considered. There are limitations inherent to the assumptions required by the input-output methodology, such as the linearity of sectoral and interregional relationships, which may mask specific intersectoral interactions within a particular agri-food product or sector. The same applies to sectoral aggregation, which in our study considers the structure given by the OECD matrices. Additionally, it is not possible to identify structural changes over a relatively short period of time, given the nature of the approach itself. Therefore, it is important to acknowledge these limitations when interpreting the results of the analysis conducted. Given that the internal geography of inter-regional value-added flows depends on the location of natural resources and service supply within the country, it is important to advance applied research that allows for the assessment of potential linkages capable of generating value for local economies. Economic geography and local sectoral patterns are important elements of analysis, and further research is needed to provide additional evidence for a more comprehensive evaluation of these issues.

Finally, despite the importance of financial services access for the development of activities in the agricultural sector, trade costs impose constraints regarding the geographical proximity between the services providers and the location of the resources industries. Thus, there is an uneven distribution of financial services concerning the location of resource-based activities. Consequently, value-added spatial patterns in financial services tend to generate a particular geography for the degree of sophistication of agricultural production at the local level.