Next Article in Journal
Optimisation of the Spraying Process of Strawberries under Varying Operational Conditions
Previous Article in Journal
Integration of Image and Sensor Data for Improved Disease Detection in Peach Trees Using Deep Learning Techniques
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Agriculture
Volume 14
Issue 6
10.3390/agriculture14060798
agriculture-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

The Relationship between Geographical Indication Products and Farmers’ Incomes Based on Meta-Analysis

by
Chunyan Li
1,
Qi Ban
2,*,
Lanqing Ge
1,*,
Liwen Qi
1 and
Chenchen Fan
1
1
Shanghai International College of Intellectual Property, Tongji University, Shanghai 200092, China
2
Postdoctoral Station of Applied Economics, Fudan University, Shanghai 200433, China
*
Authors to whom correspondence should be addressed.
Agriculture 2024, 14(6), 798; https://doi.org/10.3390/agriculture14060798
Submission received: 16 April 2024 / Revised: 19 May 2024 / Accepted: 20 May 2024 / Published: 22 May 2024
(This article belongs to the Section Agricultural Economics, Policies and Rural Management)
Browse Figures
Versions Notes

Abstract

:
Geographical indication (GI) products serve as one of the significant instruments for increasing farmers’ income. While most studies affirmatively indicate that GI products contribute to boosting farmers’ income growth, it is noteworthy that their relationship does not consistently demonstrate a positive correlation. The academic discourse on this issue remains inconclusive. This study employs a meta-analysis method to reanalyze 140 effect sizes from 32 independent research samples across diverse global contexts. The findings reveal that the development of GI products significantly promotes farmer income growth, showing a high positive correlation (r = 0.348, CI = [0.104, 0.540]). Specifically, there exists a high positive correlation between GI products and per capita disposable income (r = 0.389) and a moderate positive correlation between GI products and agricultural product prices (r = 0.255). Further analysis indicates that factors at the sample level, literature level, and methodological level all exert moderating effects on the relationship between GI products and farmers’ income. This study not only provides a scientific response to the debate surrounding the relationship between GI products and farmers’ income but also delves into the underlying mechanisms. It holds significant importance for advancing the rational optimization of agricultural resources and enhancing agricultural competitiveness.

1. Question Raised

Agricultural production is rooted in natural reproduction and intricately intertwined with economic reproduction, with specific requirements for ecological resources and environmental conditions. In regions where agriculture dominates as the leading industry, the core to achieving rural revitalization strategies and growth targets for agricultural operating income lies in fully leveraging rich regional natural resource advantages to convert these resource advantages into quality advantages, which then, through the process of economic reproduction, can be transformed into economic advantages [1]. Geographical indication (GI) products serve as an effective tool that pivots around quality advantages to convert regional resource advantages into economic advantages. As a symbol of quality and reputation, they facilitate trust-building between consumers and producers and stabilize market size and consumer base, embodying substantial market potential and wealth value. The specific quality and reputation attributes of GI products depend on the natural ecology and humanistic factors of their place of origin. This inherent uniqueness stemming from the close association with geographical environment confers upon GI products natural price advantages and an intrinsic monopolistic position [2]. Their trademark attribute conveys quality and reputation information, allowing for premium pricing and excess profits through brand recognition, ultimately raising agricultural operating income [3]. With accelerated progress in agricultural modernization, the relationship between GI products and farmers’ income has become a hot topic in agricultural development worldwide, particularly for agricultural powerhouses where the path of relying on resource consumption and low-cost labor is unsustainable for industrial sustainable development, necessitating new development strategies. As a new trend to enhance agricultural competitiveness, GI products are deemed an innovative and effective means to boost farmers’ income. However, whether the development of GI products has increased farmers’ income remains a critical question due to its significant theoretical and practical implications for promoting farmer income growth and enhancing the market competitiveness of regional products [4]. Although the European Commission resolution No. 2081/92 explicitly states that GIs can promote rural economic development in remote areas and increase farmers’ incomes, numerous empirical studies have produced inconsistent results. There are positive correlation, negative correlation, and U-shaped relationships, to no correlation, leaving the current consensus on this issue divided [5]. This not only hinders product branding development but also impacts the progression of modern agriculture. Therefore, this study aims to address three main questions: firstly, does the development of GI products contribute to raising farmers’ income? Secondly, what is the strength of this relationship? Lastly, why do existing empirical studies yield inconsistent results?
Under such circumstances, traditional qualitative methods for synthesizing related research can only categorize and summarize various empirical findings, still carrying many limitations. For example, qualitative research often relies on deep analysis within specific contexts and cases, focusing more on individual phenomena or the characteristics of certain groups, making it difficult to generalize these traits to larger populations. Therefore, there is an urgent need for a more objective research method to break through the current research impasse [6]. Existing research on the relationship between GI products and farmers’ income mainly falls into two categories: one type analyzes the theoretical mechanisms and pathways through which GIs generate economic benefits, concluding that protecting GI products can raise farmers’ earnings. The other type uses panel data or survey data to conduct empirical analyses on the relationship between GI products and farmers’ income and draws the corresponding conclusions [7].
Unlike these two types of research, meta-analysis aims to systematically synthesize and analyze numerous independent research results, seeking broadly applicable and comprehensive conclusions [8]. As a rigorous quantitative analytical method, meta-analysis serves to reanalyze previous research findings, particularly demonstrating significant application value in resolving issues with conflicting research conclusions [9]. In dealing with a multitude of empirical research results, where differing methodologies and samples lead to divergent conclusions, meta-analysis functions as a tool for systematically organizing and analyzing large quantities of quantitative literature. It treats each independent study’s findings as statistical samples, and through in-depth analysis of these various samples, meta-analysis can objectively and comprehensively reveal the characteristics of similar empirical research outcomes [10].
The marginal innovation of this study compared to previous research includes: first, unlike previous studies that focus solely on the impact of GI product development on farmers’ income, this study scientifically explores the controversy regarding the relationship between GI products and farmers’ income using meta-analysis to synthesize and re-statistically analyze empirical research findings, thereby providing a more authentic depiction of their relationship. This not only supplies scientific evidence to current research but also enriches the content and methodology in the field of GI studies. Second, this study focuses on the strength of the relationship between GI products and farmers’ income, conducting a more systematic and comprehensive analysis based on observations from different global backgrounds, offering quantitative support for boosting farmers’ income. Third, no prior research has addressed the fundamental reasons behind the discrepancies in the relationship between GI product development and farmers’ income. This study identifies potential moderating variables from the sample, literature, and methodological levels that could lead to varying research conclusions, delving into the specific contexts under which GI products affect farmers’ income differently. Against the macro backdrop of countries vigorously developing GI products to improve agricultural competitiveness, this study’s findings will hold significant implications for formulating reasonable GI protection policies and fostering new momentum for agricultural sustainable development in various countries and regions. Moreover, they can provide effective theoretical support and decision-making references for optimizing agricultural resource allocation and enhancing agricultural competitiveness. The specific research approach is as follows: firstly, develop research hypotheses and an analysis framework through a literature review. Secondly, strictly adhere to the steps of meta-analysis to screen literature, calculate effect sizes, and explore heterogeneity. Thirdly, analyze the research results. Finally, present the results and discussions.

2. Theoretical Background and Research Hypotheses

2.1. Impact of GI Products on Farmers’ Income and Its Subdimensions

Endogenous growth theory underscores the central role of knowledge and technology in economic growth [11]. On one hand, GI, as a form of intellectual property, represents the uniqueness and quality guarantee of products from a specific region, contributing to enhancing the brand value and market recognition of products, promoting product branding and knowledge-based transformation [12]. This brand value enhancement can result in premium effects, enabling farmers to fetch higher returns during sales [13]. On the other hand, the agricultural industry chain spans from production to processing, sales, and beyond. The promotion and utilization of GIs can optimize the structure and function of the agricultural industry chain, facilitating further processing and refining of products and thereby increasing product added-value and market competitiveness. By participating in the high-value-added segments of the industry chain, farmers can share more in the value-added gains, resulting in income growth [14].
Numerous empirical studies support the positive influence of GI products on farmers’ income, arguing that GI products, predominantly agricultural products, benefit from the high dependence of agricultural production on natural resources and the influence of geographical location and resource endowments. The collective rights attribute and regional exclusivity of GI products imply that producers in these areas can exclude others, thereby gaining corresponding economic benefits. This necessitates fair distribution of benefits among GI producers and their groups. Through agricultural production, comparative advantages in natural resources directly translate into farmers’ income [15]. Generally, GI products are often associated with specific regions and production methods. Farmers can enhance product quality by adopting more advanced agricultural techniques, stricter production standards, and quality control measures, thereby increasing consumer recognition and willingness to purchase [16]. This brings additional economic value to the products, which may stimulate producers to improve product quality and expand production scale. The successful promotion and sale of GI products help increase product prices and per capita disposable income, ultimately assisting farmers in obtaining higher profits from selling GI products [17].
On the one hand, with the market promotion of GI products and the improvement of consumer awareness, product market share and sales channels can be expanded, thereby increasing sales volume. By expanding online and offline sales channels, farmers can sell products to a wider range of regions and consumer groups, achieving growth in sales revenue [18]. In addition, through training and education, farmers can improve production skills and market awareness, better participating in the production and sales of GI products. This can not only improve product quality and competitiveness but also create more employment opportunities and income sources in rural areas, attract more labor force participation, improve the employment stability of rural residents, and increase their per capita disposable income [19]. On the other hand, the theory of product differentiation emphasizes the existence of non-complete substitutability among various products. GI products, with their unique regional characteristics and quality assurance, possess differentiated characteristics distinct from other products [20]. This uniqueness enables them to stand out among many similar products, meeting consumers’ pursuit of distinctive and high-quality products. As a special brand resource, it helps enhance product awareness and reputation. Through brand building and management, their unique geographical and production conditions give these products comparative advantages in certain aspects [21]. Consumers generally believe that these products undergo rigorous production and quality control, thus possessing higher quality and better taste [22]. This trust and loyalty can translate into higher product prices because consumers are willing to pay more for high-quality products [23]. Therefore, the prices of GI products often include a premium for cultural and emotional value.
Therefore, this study proposes the following hypotheses:
H1: 
The development of GI products can effectively promote farmers’ income growth.
H1a: 
The development of GI products can effectively promote per capita disposable income growth.
H1b: 
The development of GI products can effectively promote agricultural product prices.
Based on the theoretical analysis and research hypotheses above, the basic framework of this study is derived, as shown in Figure 1.

2.2. Moderating Factors Influencing the Relationship between GI Products and Farmer Incomes

2.2.1. Sources of Sample-Level Differences

Different countries of sample origin: countries worldwide are actively leveraging the advantages of GI products to promote industrial development, enhance product quality and reputation, and strengthen national competitiveness. However, the characteristics of GI product development vary among countries due to their unique national contexts [24]. Many countries with a long history of GI product development, such as France and Italy, not only represent local culture and tradition but also serve as important brands in the international market. Compared to these countries, the Chinese government started protecting GI products relatively late but has rapidly accelerated their development [25]. As of now, China has over 10,075 registered GI products, far surpassing other countries. This achievement is attributed to the Chinese government’s high attention and policy support for GI product development. For instance, the Ministry of Agriculture and Rural Affairs, in conjunction with the Ministry of Finance and other departments, has implemented a GI agricultural product protection project, providing financial support to promote the protection and development of GI products [26]. The continuity and stability of such policies provide strong guarantees for the development of GI products. However, Joosse (2021) found through spatial modeling analysis that GI did not bring price advantages to products in less developed areas and did not contribute to farmer income growth [27]. Conversely, Xiao (2021) found through panel data analysis of GI registration quantity in China that GI products have a strong positive effect on regional agricultural economic development and farmer income [28]. Therefore, differences in the development of GI products among countries may affect the relationship between GI products and farmer incomes.
Differences in the regional scope and sample type of the study: studies conducted at the national level provide more extensive and universal results, while regional-level studies are essential for investigating regional issues [29]. Differences in resource endowments and policy space between national and regional studies directly influence the results of the relationship between GI products and farmer incomes. Schober’s survey of 150 respondents at the regional level found that GI products are increasingly favored by consumers due to their unique regional characteristics, excellent quality, and profound cultural heritage, leading to enhanced competitiveness in the market [30]. Conversely, Sorgho’s analysis using a national sample found that GI did not confer higher value to products in international trade and did not affect farmer incomes. Therefore, differences in the regional scope of the study sample may influence the relationship between GI products and farmer incomes [31]. Additionally, there is variation in scholars’ research approaches: some scholars use the total quantity of GI products in a country or region as the sample, while others use specific products as the sample. Depending on the type of product analyzed, research results on the relationship between GI products and farmer incomes may vary. For example, Vakoufaris (2022) found that Italian high-quality wines protected by GI could command higher market prices [32]. GI protection encourages farmers and producers to adhere to traditional brewing methods and maintain product uniqueness and high quality, and also provides them with more market opportunities and economic benefits. This has positive implications for maintaining regional ecological balance and increasing farmer incomes [33]. Conversely, Zhang ‘s model, based on analysis using the total quantity of GI products, found that although GI products have certain advantages, the market is crowded with similar products, leading to fierce competition. If farmers fail to seize market opportunities and improve product quality and competitiveness, the advantages of GI products may be weakened, thereby affecting farmer incomes [34].

2.2.2. Sources of Differences in Literature-Level Relationships

Differences in journal types: this study includes both journal articles and dissertations. Journal articles typically undergo rigorous peer review to ensure quality and academic value, but they often have strict length limitations, which may hinder the comprehensive presentation of the research process and results. Additionally, the authors of journal articles are more diverse, including university faculty and students, as well as participants in social practice activities, collectively promoting academic research and social development [35]. Dissertations, on the other hand, are authored by graduate students under the guidance of mentors, allowing for comprehensive research on specific fields or issues without strict length limitations, thereby enabling full presentation of the research process and results. Differences between journal articles and dissertations may influence the relationship between GI products and farmer incomes [36].
Differences in journal quality: journals with higher impact factors may prioritize innovative research findings and significant statistical results. Preferences for different types of research on the relationship between GI products and farmer incomes may stem from the specific reader base and academic positioning of each journal [37]. Some journals may focus more on theoretical exploration and model construction, while others may prefer empirical research and case studies. These differences not only reflect the academic tendencies of the journals but also demonstrate the continuous deepening of academic understanding of this complex relationship [38]. Therefore, differences in journal quality may influence the relationship between GI products and farmer incomes.
Differences in publication years: over different years, due to various factors such as research foundations and policy environments, scholars’ studies on the relationship between GI products and farmer incomes may focus on different aspects, leading to diverse research outcomes [39]. Additionally, academic research tends to accumulate and deepen over time, with new research questions and directions emerging, while older studies may gradually fade. Newer papers may build on previous research, possessing richer knowledge backgrounds to enhance research accuracy and reliability. In contrast, earlier papers may use more traditional or basic research methods [40]. Furthermore, papers published in different years may use different data sources and analysis methods. As technology advances and data availability increases, newer papers may use more extensive and detailed datasets and employ more advanced data analysis methods, leading to differences in conclusions and deeper insights [41].

2.2.3. Sources of Differences in Methodological Approaches

On the one hand, there are different research methods: existing literature involves two main categories of research methods, namely, multiple linear regression analysis and other methods. Different research methods have certain differences in assumptions and applicability, which may lead to diversity in research results [42]. For instance, Stanley (2021) used multiple linear regression analysis to analyze the economic benefits of GI products, finding that unique GI products often have unique flavors, quality, or production processes, giving them a competitive advantage in the market and attracting consumers willing to pay higher prices, thereby contributing to increased farmer incomes [43]. Conversely, Chaney (2008) found through the use of a random forest model and panel data analysis that although some GI products have excellent quality, consumer demand for them is limited. This limits the expansion of these products’ market share, making it difficult to promote farmer income growth [44]. Therefore, differences in research methods may influence the relationship between GI products and farmer incomes. On the other hand, there are different types of data: existing literature involves mainly panel data and cross-sectional data. Panel data contain multiple time observations of the same individual, providing more data points for estimating complex behavioral equations, enabling researchers to capture changes over time. Cross-sectional data describe the characteristics of individuals or groups at a specific point in time, such as population structure and socioeconomic status [45]. Differences in data types in existing studies may lead to biases in research results. Qie (2023) analyzed county-level panel data from 2006 to 2020 and found that the promotion of agricultural economy by GI products is influenced by regional economic development, resulting in differences between the eastern and western regions [46].
To explore the impact of the above factors on the relationship between GI products and farmer incomes, this study posits:
H2: 
Differences in sample level, literature level, and method level will moderate the relationship between GI products and farmer incomes.

3. Methodology

This study systematically reviews the literature on the relationship between geographical indications and farmer incomes using the meta-analysis research technique proposed by Glass in 1976 [47]. The advantages of this method lie in providing comprehensive final results based on the study outcomes, offering information on the magnitude of effects, and strict data selection requirements, ensuring scientific and accurate results. Specifically, this study utilizes STATA 17 software to examine the effects of geographical indications and their dimensions on farmer incomes. Additionally, this study investigates the moderating effects of different factors on the relationship between geographical indications and farmer incomes from the sample level, literature level, and method level [48]. The research design is outlined in Figure 2.

3.1. Literature Retrieval and Screening

This study comprehensively searched Chinese and English literature until February 2024. Chinese literature was retrieved from databases such as CNKI, Wanfang, and VIP journals, while English literature was retrieved from databases such as Web of Science, ScienceDirect, Springer, and ProQuest, using relevant terms such as “geographical indication”, “geographical indication protection”, “geographical indication product”, “farmer income”, “rural economy”, “poverty alleviation”, “wealth creation”, and “employment”. The preliminary literature search provided a sufficiently broad range of data documents. Furthermore, to avoid omissions, this study supplemented the search with relevant reviews and meta-analyses for additional references. Through these steps, a total of 7889 initial literature records were obtained. Combining the requirements of the meta-analysis method and the research topic, two independent screeners conducted sequential screening of titles, abstracts, and full texts through multiple steps and included literature in the study. All included literature had to meet the following criteria simultaneously: (1) reporting empirical research with specific experimental steps, excluding purely theoretical and literature review articles; (2) containing at least one relevant relationship between geographical indications and farmer incomes or other indicators that can be transformed into effect sizes; and (3) having mutually independent samples among studies. After the screening, a total of 32 articles met the criteria, including 17 Chinese articles and 15 English articles; 18 journal articles; and 14 dissertations. Since some research documents contain multiple independent effect sizes, this study obtained a total of 140 independent samples. See Figure 3 for the specific literature screening process. Specific information of included literature is presented in Table 1.

3.2. Literature Encoding

This study encoded the literature included in the meta-analysis, including literature information (title, author, and publication date), sample time span, sample size, research area, journal quality, data type, research method, effect size, etc. Variables such as sample country, regional scope, sample type, journal type, journal quality, publication year, research method, and data type will be used as moderating variables in subsequent analyses. The encoding work of this study was independently completed by two researchers. After formulating coding rules, the two researchers independently coded the papers by reading the full text. After coding, the two researchers compared the coding contents and discussed any differences until a final consistent coding was achieved.

4. Meta-Analysis Results

4.1. Publication Bias Test

Table 2 shows test of publication bias. During the meta-analysis process, special attention needs to be paid to publication bias [49]. The assumption is that studies with small effect sizes are more difficult to publish compared to those with large effect sizes. Therefore, it is necessary to test for this to ensure the accuracy and reliability of the results. This study used the fail-safe coefficient method to test for publication bias, and the result showed a fail-safe coefficient of 1218, significantly greater than 505 (5k + 10), indicating no significant publication bias in this study. Additionally, from the perspective of per capita disposable income and agricultural product price increase, the obtained fail-safe coefficient was also greater than the critical value. Therefore, it can be considered that the results generated by the samples in this study are scientific and accurate.

4.2. Relationship between GI Products and Farmer Incomes

In meta-analysis, to select an appropriate model for estimating effect sizes, the heterogeneity of the samples needs to be considered. When sample heterogeneity is high, a random-effects model is usually adopted, while a fixed-effects model is more suitable when the samples are relatively homogeneous [50]. Through heterogeneity tests conducted on the included effect sizes, we found that both overall and subtype GI products exhibited high heterogeneity. Overall, the heterogeneity test result for the relationship between GI products and farmer incomes was Q = 50,181.92 (p < 0.05), I2 = 99.83, indicating that approximately 99.83% of the observed variation in the model comes from true differences in effect sizes, with about 1.17% originating from random error. Therefore, the relationship between the two was confirmed through the heterogeneity test. Similarly, from the perspectives of GI products and per capita disposable income, as well as GI products and agricultural product price increases, the corresponding I2 and Q values both indicated a high degree of heterogeneity in their relationships. Hence, subsequent studies will analyze using a random-effects model, and it is necessary to explore the moderating effects of variables on the relationship between GI products and farmer incomes.
Table 3 summarizes the meta-analysis results of the correlation coefficients between GI products and farmer incomes. It was found that the development of GI products is significantly positively correlated with farmer incomes (r = 0.348, 95%CI = [0.104, 0.540]). Referring to the standards set by Gignac and Szodorai (2016), this study interprets correlation coefficient magnitudes where 0.1 < r < 0.2, 0.2 < r < 0.3, and r > 0.3 are considered low, moderate, and high correlations, respectively [51]. According to this standard, this study believes that GI products have a highly positive impact on farmer incomes. Furthermore, we divided farmer incomes into per capita disposable income and agricultural product price increases for further analysis. The relationship between GI products and per capita disposable income was highly positively correlated (r = 0.389, 95%CI = [0.056, 0.644]), while the relationship between GI products and agricultural product price increases showed a moderate positive correlation (r = 0.255, 95%CI = [0.214, 0.296]). Therefore, research hypotheses H1, H1a, and H1b are supported.

4.3. Moderation Analysis

After conducting heterogeneity tests, we found significant heterogeneity characteristics in the relationship between GI products and farmer incomes, indicating that this relationship may be influenced by certain potential moderating variables. To further explore this mechanism of influence, this study coded and analyzed the collected information and conducted subgroup analyses. Detailed research results are shown in Table 4. At the sample level, country differences, regional scope, and sample type all significantly moderate the relationship between GI products and farmer incomes (p < 0.05). In the context of China, the correlation between GI products and farmer incomes (r = 0.412) is significantly higher than in other countries (r = 0.208), demonstrating a high degree of correlation. This result indicates that GI products in China play a significant role in promoting farmer incomes. Through comparative analysis between national and specific regional situations, we found that the correlation coefficient obtained from specific regional samples is as high as 0.455, significantly higher than that of national samples (r = 0.246). These data suggest that within specific regional scopes, GI products have a more significant impact on farmer incomes. By selecting specific GI products as research samples, we can obtain larger effect sizes (r = 0.400). At the literature level, journal type, journal quality, and publication year significantly moderate the relationship between GI products and farmer incomes (p < 0.05). Compared to dissertations, articles published in journals are more likely to have a significantly positive impact (r = 0.562), showing a highly positive correlation. Additionally, the results indicate that high-quality journals are more likely to publish articles with positive relationships. Older literature is more likely to publish studies with stronger correlation conclusions (r = 0.635). At the method level, research methods and data types both moderate the relationship between GI products and farmer incomes (p < 0.05). On one hand, using multiple linear regression (r = 0.329) results in a slightly weaker positive correlation compared to other methods (r = 0.360). On the other hand, the strength of the relationship between GI products and farmer incomes under panel data samples (r = 0.332) is significantly higher than under cross-sectional data (r = 0.332). Based on the above analysis, hypothesis H2 is confirmed.

5. Conclusions and Implications

5.1. Research Conclusions

This study employs meta-analysis to delve into the relationship between GI products and farmer incomes, leveraging a wide array of cross-contextual data samples. With stringent control over publication biases, the research thoroughly investigates the nexus between GI products and farmer incomes from sample, literature, and methodological perspectives, dissecting the potential influences of various factors such as national backgrounds, sample types, literature quality, and research methodologies on this relationship. Through an in-depth integrated examination of the impact mechanism of GI products on farmer incomes and their boundary effects, the study arrives at interim conclusions from the meta-analysis of GI products, further enriching the research findings in the relevant field.
There exists a significant positive correlation between the development of GI products and farmer incomes. Specifically, a highly positive correlation is observed between GI products and per capita disposable income. Concurrently, a moderately positive correlation is noted between GI products and agricultural product price increases. This finding suggests that GI products play a pivotal role in enhancing per capita disposable incomes among farmers and, to a certain extent, drive agricultural product price increases, thereby effectively promoting farmer income growth. This conclusion holds significant implications for optimizing agricultural industry structures and elevating farmer income levels. As a unique form of intellectual property protection, GI not only safeguards specific regional products but also brings tangible benefits to farmers [52]. On one hand, GI facilitates the deep processing of agricultural products and the expansion of the industrial chain, thereby creating more income channels for farmers. As the industrial chain expands and improves, it promotes the coordinated development of multiple sectors including agriculture, industry, and services, generating synergistic effects across industries and creating more employment opportunities. This process enhances rural employment stability and increases farmers’ disposable incomes. On the other hand, the robust premium mechanism of GI is primarily derived from its collective intellectual property attributes, representing the common interests of multiple producers in a given region. Due to their unique regional characteristics and quality commitments, GI products are preferred by consumers, leading to increased market demand and subsequent price increases, thereby yielding premium returns for producers. Moreover, the premium mechanism is closely intertwined with its role in cultural heritage. By preserving and leveraging GI, local traditional cultures can be inherited and promoted, enhancing regional cultural identity and cohesion. This cultural heritage adds unique charm to GI products, increasing their market acceptance and premium space. Strengthening the protection and regulation of GI is crucial for enhancing farmers economic benefits. To achieve this goal, cooperation among governments, enterprises, and consumers is essential to promote the widespread dissemination and promotion of GI products, enabling more people to understand and recognize the unique characteristics and values of these goods [53].
Significant national differences exist in the relationship between the development of GI products and farmer incomes. The role of GI in promoting income growth among farmers in China is significantly superior to that in other countries. This can be attributed to two main factors. First, as an agricultural powerhouse, China boasts a vast rural population, with agriculture playing a crucial role in the national economy. Against this macro backdrop, GI plays a pivotal role in increasing farmer income levels. Extensive promotion of GI can effectively stimulate the intrinsic motivation of farmers to participate in the production, processing, and sale of GI agricultural products, diversifying their sources of income and creating more employment opportunities [54]. This measure holds profound significance for promoting rural economic development and improving farmers’ living standards. Second, the Chinese government has implemented various measures to promote the protection and development of GI, including constructing a complete legal framework, enhancing supervision and enforcement, and promoting the publicity and popularization of GI brands. In particular, promotional activities for GI brands have significantly increased farmers’ awareness of the importance of GI, sparking their enthusiasm to participate in the production and sale of GI products. By actively engaging in the production and sale of GI products, farmers not only significantly improve the quality and popularity of products but also steadily increase their incomes [55].
The relationship between the development of GI products and farmer incomes is subject to regional scope moderation. The results indicate that, compared to the national scope, the impact of GI products on farmer incomes is more significant in specific regions. This finding reveals the differentiated effects of different GI products on farmer incomes in various regions. GI products typically possess unique regional characteristics and quality, determined by factors such as local natural environment, climatic conditions, and traditional craftsmanship [56]. This uniqueness enhances the market recognition and competitiveness of GI products, thereby providing higher economic returns for farmers. However, considering the rich diversity and widespread distribution of GI products across the country, the relationship effects between these products and farmer incomes also exhibit diversified characteristics. Aggregating various nationwide data may produce a relatively neutral effect value. Therefore, precise delineation of regional scopes helps to more accurately grasp the positive role of GI products in increasing farmer incomes [57]. Similarly, sample type significantly moderates the relationship between GI products and farmer incomes. Specific GI products exhibit more pronounced effects on increasing farmer incomes compared to the total GI product quantity. This is because researchers typically select specific GI products with significant characteristics and broad market potential as research objects. These products, due to their unique regional characteristics, quality assurance, and cultural connotations, are more likely to form a unique brand image in the minds of consumers, thus enjoying higher market recognition and competitiveness. This brand effect helps to enhance the added value of products, bringing higher sales income to farmers.
The type of literature causes significant differences in the relationship between GI products and farmer incomes. The results show that papers published in journals are more likely to yield significant positive impact conclusions. Journals garner widespread recognition and respect due to their rigorous academic review and peer review processes. These journals tend to publish studies with distinct viewpoints and outstanding achievements. Conversely, research with less significant experimental results or dissenting from mainstream academic viewpoints may face certain limitations in publication opportunities. Furthermore, the quality of journals moderates the relationship between GI products and farmer incomes. High-quality journals typically possess broader academic influence and reader bases. To maintain sustained academic influence, these journals pay more attention to the significance of statistical results and the innovation of research conclusions. Additionally, publication year causes a certain degree of difference in the positive impact of GI products on farmer incomes. Unexpectedly, studies before 2015 yield higher effect values than recent ones. This is because early studies may be constrained by data availability and relatively limited research methods. Before 2015, due to limitations in data collection and analysis techniques, researchers often relied more on basic statistical methods and intuitive case analysis to explore the relationship between GI products and farmer incomes. Since other potential complex factors and variables were not comprehensively considered, these studies may more easily conclude a positive relationship between the two. Furthermore, the development of GI products has gradually matured over time, and market competition has become increasingly fierce. Compared to earlier studies, current research focuses more on complex issues such as market positioning, brand building, and industrial chain development. When exploring the relationship between GI products and farmer incomes, researchers have identified more influencing factors and variables, leading to diversified conclusions, and the positive relationship is no longer the sole or dominant viewpoint.
Research methods significantly moderate the relationship between GI products and farmer incomes. The methods used to study the relationship between GI products and farmer incomes are diverse, including but not limited to multiple linear regression, difference-in-differences (DID), and analysis of variance. The results show that the positive correlation revealed by multiple linear regression methods is slightly lower compared to other analysis methods. The characteristics of multiple linear regression methods determine the robustness and conservatism of their results. Due to the presence of endogeneity issues, multiple linear regression may not directly or significantly demonstrate the positive correlation between GI products and farmer incomes as some simpler methods do. Additionally, multiple linear regression also requires consideration of model selection and setup issues. If the model setup is unreasonable or important explanatory variables are omitted, regression results may be biased. When the impact of GI products on farmer incomes is interfered with by other unmodeled factors, the effect values between the two may be underestimated or concealed. Furthermore, data type significantly moderates the relationship between GI products and farmer incomes. Effect values generated from panel data samples are higher compared to cross-sectional data. In cross-sectional data, differences between different observation objects may be significant, leading to estimation biases. Panel data, by introducing a time dimension, can distinguish individual fixed effects and random effects, thereby better controlling this heterogeneity. Therefore, panel data can more comprehensively capture the dynamic changes and mutual effects between GI products and farmer incomes, thereby more accurately revealing their positive correlation.

5.2. Research Implications

This study utilizes meta-analysis to conduct an in-depth investigation into the relationship between GI products and farmer incomes. Overall, a highly positive correlation is found between GI products and farmer incomes, supporting hypothesis H1 and the results of most current studies. This indicates the significant role of GI products in promoting increased incomes among farmers. Furthermore, the study finds that the correlation between GI products and per capita disposable income is highly positive, with the correlation coefficient exceeding that of GI products and agricultural product price increases. This result reflects consumer recognition and favoritism towards GI products, which are highly sought after due to their unique quality and regional characteristics. This increased market demand further drives the development of the GI product industry and brings more economic benefits and development opportunities for farmers. Therefore, policymakers should attach great importance to the cultivation and development of GI products. For example, special funds for GI projects can be set up to provide strong support for the research, promotion, and market expansion of GI products. It will help improve the market competitiveness of GI products and further expand their market share, bringing higher incomes to farmers. Preferential policies such as tax breaks and exemptions can also be provided to enterprises producing geographical indication products, thereby increasing the added value of geographical indication products. In addition, the government can establish a comprehensive standard system and regulatory mechanism for GI products to safeguard the quality and reputation. By organizing experts to conduct a strict review of GI products, it can prevent counterfeit and shoddy products from entering the market and safeguard consumers’ rights and interests.
Production entities should increase their efforts to cultivate and develop GI products with a view to realizing sustainable agricultural development. GI products are usually closely related to the local natural environment and resource endowment. The development process needs to follow green, low-carbon, and sustainable principles. Therefore, the development of GI products allows for better protection and utilization of agricultural resources and realizes the green and sustainable development of agriculture.
The high value and market demand of GI products can stimulate the enthusiasm of farmers in planting and breeding, further optimizing the structure of agricultural industry. The development of GI products acts as a chain, closely connecting all related industries. It contributes to the diversified development of the rural economy and improves the overall economic development of the countryside. With the development of the GI industry, more and more employment opportunities arise. Such a development trend can attract the return of rural laborers and reduce the loss of rural population, thus promoting the stability and prosperity of rural society.

5.3. Limitations

This study aims to deeply explore the impact of GI products on farmer incomes, complementing the shortcomings of meta-analysis in explaining the logical relationship between variables by introducing endogenous growth theory. Additionally, the study contrasts the different impacts of GI products on various aspects of farmer incomes and conducts a thorough analysis of their underlying logical differences. To further ensure the comprehensiveness and accuracy of the study, the research conducts subgroup analysis tests on relevant moderating variables from three levels: samples, literature, and methodology, to construct a more complete and rigorous research framework. The limitations of this paper are mainly as follows: firstly, although this study collects literature from various public databases to conduct a meta-analysis, some literature does not report basic descriptive statistics and correlation coefficients. This resulted in the inability to include it in the meta-analysis and the loss of some samples. Secondly, due to the limitations of meta-analysis methods, this study only analyzes the linear relationship between GI products and farmer incomes. In the future study, the following directions can be tried. Firstly, the study of globalization and localization of GI products and research on how GI products maintain their uniqueness and regional features in the context of globalization, while exploring how to integrate them into the global market. Secondly, study on the protection of intellectual property rights of GI products and examining the laws and regulations as well as the practical experience of various countries in the protection of intellectual property rights of GI products and putting forward suggestions for improving the intellectual property protection system. Thirdly, study on the connection between geographical indication products and rural revitalization and exploring the role and value of GI products in rural revitalization and analyzing how to promote rural economic development and cultural inheritance through the development of GI products. Finally, proposing GI product development strategies to promote rural revitalization.

Author Contributions

Conceptualization, C.L. and Q.B.; Methodology, C.L. and Q.B.; Software, C.L. and L.G.; Validation, C.L. and L.G.; Formal analysis, C.L. and Q.B.; Investigation, L.Q. and C.F.; Resources, C.L. and Q.B.; Data curation, L.G.; Writing—original draft, C.L. and L.Q.; Writing—review & editing, C.L., Q.B., L.G. and L.Q.; Visualization, L.Q. and C.F.; Supervision, Q.B. and L.G.; Project administration, L.Q. and C.F. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Social Science Fund Project (16ZDA236); Pujiang Talent Program Project (22PJC113); Soft Science Research Project under the Shanghai Science and Technology Innovation Action Plan (23692116300).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data is contained within the article.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Ay, J.S.; Diallo, A.; Pham, H.V. Wine prices capitalization in vineyard prices of Côte-d’Or. Rev. Econ. 2023, 74, 115–135. [Google Scholar]
  2. Glogovetan, A.I.; Dabija, D.C.; Fiore, M.; Pocol, C.B. Consumer Perception and Understanding of European Union Quality Schemes: A Systematic Literature Review. Sustainability 2022, 14, 1667. [Google Scholar] [CrossRef]
  3. Reddy, A.A.; Melts, I.; Mohan, G.; Rani, C.R.; Pawar, V.; Singh, V.; Choubey, M.; Vashishtha, T.; Suresh, A.; Bhattarai, M. Economic Impact of Organic Agriculture: Evidence from a Pan-India Survey. Sustainability 2022, 14, 15057. [Google Scholar] [CrossRef]
  4. Lawal-Arowolo, A. Geographical indications and cultural artworks in Nigeria: A cue from other jurisdictions. J. World Intellect. Prop. 2019, 22, 364–374. [Google Scholar] [CrossRef]
  5. Henry, L. Adapting the designated area of geographical indications to climate change. Am. J. Agric. Econ. 2022, 105, 1088–1115. [Google Scholar] [CrossRef]
  6. Haubrock, P.J.; Oficialdegui, F.J.; Zeng, Y.W.; Patoka, J.; Yeo, D.C.J.; Kouba, A. The redclaw crayfish: A prominent aquaculture species with invasive potential in tropical and subtropical biodiversity hotspots. Rev. Aquac. 2021, 13, 1488–1530. [Google Scholar] [CrossRef]
  7. Reddy, A.A. Electronic national agricultural markets: The way forward. Curr. Sci. 2018, 115, 826–837. [Google Scholar] [CrossRef]
  8. Deconinck, K.; Swinnen, J. The Size of Terroir: A Theoretical Note on Economics and Politics of Geographical Indications. J. Agric. Econ. 2021, 72, 321–328. [Google Scholar] [CrossRef]
  9. Curzi, D.; Huysmans, M. The Impact of Protecting EU Geographical Indications in Trade Agreements JEL codes. Am. J. Agric. Econ. 2022, 104, 364–384. [Google Scholar] [CrossRef]
  10. Besah-Adanu, C.; Bosselmann, A.S.; Hansted, L.; Kwapong, P.K. Food origin labels in Ghana: Finding inspiration in the European geographical indications system on honey. J. World Intellect. Prop. 2019, 22, 349–363. [Google Scholar] [CrossRef]
  11. Durand, C.; Fournier, S. Can Geographical Indications Modernize Indonesian and Vietnamese Agriculture? Analyzing the Role of National and Local Governments and Producers’ Strategies. World Dev. 2017, 98, 93–104. [Google Scholar] [CrossRef]
  12. Prata-Sena, M.; Castro-Carvalho, B.M.; Nunes, S.; Amaral, B.; Silva, P. The terroir of Port wine: Two hundred and sixty years of history. Food Chem. 2018, 257, 388–398. [Google Scholar] [CrossRef] [PubMed]
  13. Hellegers, P. Food security vulnerability due to trade dependencies on Russia and Ukraine. Food Secur. 2022, 14, 1503–1510. [Google Scholar] [CrossRef] [PubMed]
  14. Oke, E.K. Rethinking Nigerian geographical indications law. J. World Intellect. Prop. 2022, 25, 746–752. [Google Scholar] [CrossRef]
  15. Roselli, L.; Giannoccaro, G.; Carlucci, D. EU Quality Labels in the Italian Olive Oil Market: How Much Overlap is There Between Geographical Indication and Organic Production? J. Food Prod. Mark. 2018, 24, 784–801. [Google Scholar] [CrossRef]
  16. Santos, J.F.; Ribeiro, J.C. Product Attribute Saliency and Region of Origin: Some Empirical Evidence from Portugal Product. In Proceedings of the 99th Seminar of the EAAE, Copenhagen, Denmark, 24–27 August 2005. [Google Scholar]
  17. Zhang, S.; Sun, Y.; Wang, Y.; Lin, X. Geographical indication, agricultural development and the alleviation of rural relative poverty. Sustain. Dev. 2024. [Google Scholar] [CrossRef]
  18. Xu, Z.Y.; Feng, Y.; Wei, H. Does Geographical Indication Certification Increase the Technical Complexity of Export Agricultural Products? Front. Environ. Sci. 2022, 10, 892632. [Google Scholar] [CrossRef]
  19. Qian, W.W.; Dong, Y.G. Comparative study on the geographical indication protection between China and the European Union-From the perspective of the China-EU Geographical Indications Agreement. Agric. Econ.-Zemed. Ekon. 2023, 69, 185–201. [Google Scholar] [CrossRef]
  20. Handler, M. Geographical Indications at the Crossroads of Trade, Development and Culture: Focus on Asia-Pacific. Queen Mary J. Intellect. Prop. 2019, 9, 122–124. [Google Scholar] [CrossRef]
  21. Haeck, C.; Meloni, G.; Swinnen, J. The Value of Terroir: A Historical Analysis of the Bordeaux and Champagne Geographical Indications. Appl. Econ. Perspect. Policy 2019, 41, 598–619. [Google Scholar] [CrossRef]
  22. Slade, P.; Michler, J.D.; Josephson, A. Foreign geographical indications, consumer preferences, and the domestic market for cheese. Appl. Econ. Perspect. Policy 2019, 41, 370–390. [Google Scholar] [CrossRef]
  23. Zhang, S.J.; Fang, K.X.; Ding, Z.A.; Wu, J.X.; Lin, J.Z.; Xu, D.M.; Zhong, J.S.; Xia, F.; Feng, J.H.; Shen, G.P. Untargeted Metabolomics Analysis Revealed the Difference of Component and Geographical Indication Markers of Panax notoginseng in Different Production Areas. Foods 2023, 12, 2377. [Google Scholar] [CrossRef] [PubMed]
  24. Ay, J.S. The Informational Content of Geographical Indications. Am. J. Agric. Econ. 2021, 103, 523–542. [Google Scholar] [CrossRef]
  25. Nguyen, S.L.; Le, V.A. Diffusion of Geographical Indication Law in Vietnam: “Journey To The West”. IIC-Int. Rev. Intellect. Prop. Compet. Law 2023, 54, 176–199. [Google Scholar] [CrossRef]
  26. Wen, H.; Abbas, S. The relationship between symbolic agricultural products and agricultural economic development based on numerical analysis. Math. Probl. Eng. 2022, 2022, 4971437. [Google Scholar] [CrossRef]
  27. Joosse, S.; Olders, P.; Boonstra, W.J. Why are geographical indications unevenly distributed over Europe? Br. Food J. 2021, 123, 490–510. [Google Scholar] [CrossRef]
  28. Xiao, R.; Zhao, P.; Qi, Y.; Lu, Y. The spatial heterogeneity characteristics and the influencing factors of the Agro-product Geographical Indication Brands. Res. Agric. Mod. 2021, 42, 1126–1136. [Google Scholar]
  29. Lubinga, M.H.; Ngqangweni, S.; Walt, S.V.D.; Potelwa, Y.; Ntshangase, T. Geographical indications in the wine industry: Does it matter for South Africa? Int. J. Wine Bus. Res. 2020. ahead-of-print. [Google Scholar] [CrossRef]
  30. Schober, K.; Balling, R.; Chilla, T.; Lindermayer, H. European Integration Processes in the EU GI System-A Long-Term Review of EU Regulation for GIs. Sustainability 2023, 15, 2666. [Google Scholar] [CrossRef]
  31. Sorgho, Z.; Larue, B. Do geographical indications really increase trade? a conceptual framework and empirics. J. Agric. Food Ind. Organ. 2017, 16, 20170010. [Google Scholar] [CrossRef]
  32. Vakoufaris, H.; Gocci, A. Geographical Indications and Sustainable Development: An Assessment of Four Categories of Products from the Fruit and Vegetable Sector of the Eu. Food Rev. Int. 2022, 39, 7112–7125. [Google Scholar] [CrossRef]
  33. Ittersum. The Role of Region of Origin in Consumer Decision-Making and Choice; Wageningen University and Research: Wageningen, The Netherlands, 2001. [Google Scholar]
  34. Zhang, S.; Sun, Y.; Yu, X.; Zhang, Y. Geographical Indication, Agricultural Products Export and Urban-Rural Income Gap. Agriculture 2023, 13, 378. [Google Scholar] [CrossRef]
  35. Iraizoz, B.; Bardají, I.; Rapún, M. Do ‘protected geographical indications’ (pgi)-certified farms perform better? The case of beef farms in spain. Outlook Agric. 2011, 40, 125–130. [Google Scholar] [CrossRef]
  36. Liu, H.-J. Spatial distribution characteristics of geographical indications and brand spillover effects: An empirical study based on the geographical indication data of 3 departments in China. J. Financ. Econ. 2011, 37, 49–58. [Google Scholar]
  37. Sgroi, F. Territorial development models: A new strategic vision to analyze the relationship between the environment, public goods and geographical indications. Sci. Total Environ. 2021, 787, 147585. [Google Scholar] [CrossRef] [PubMed]
  38. Mwakaje, S.J. Protection of geographical indications and cross-border trade: A survey of legal and regulatory frameworks in East Africa. J. World Intellect. Prop. 2022, 25, 31–44. [Google Scholar] [CrossRef]
  39. Ntakiyisumba, E.; Lee, S.; Won, G. Identification of risk profiles for Salmonella prevalence in pig supply chains in South Korea using meta-analysis and a quantitative microbial risk assessment model. Food Res. Int. 2023, 170, 112999. [Google Scholar] [CrossRef] [PubMed]
  40. Bourdin, A.; Dokhelar, T.; Bord, S.; Van Halder, I.; Stemmelen, A.; Scherer-Lorenzen, M.; Jactel, H. Forests harbor more ticks than other habitats: A meta-analysis. For. Ecol. Manag. 2023, 541, 121081. [Google Scholar] [CrossRef]
  41. Kneller, E. EU-Australia FTA: Challenges and potential points of convergence for negotiations in geographical indications. J. World Intellect. Prop. 2020, 23, 546–578. [Google Scholar] [CrossRef]
  42. Coggins, S.; Malone, B.P.; Stockmann, U.; Possell, M.; McBratney, A.B. Towards meaningful geographical indications: Validating terroirs on a 200 km2 scale in Australia’s lower Hunter Valley. Geoderma Reg. 2019, 16, e00209. [Google Scholar] [CrossRef]
  43. Stanley, T.D. Wheat from chaff: Meta-analysis as quantitative literature review. J. Econ. Perspect. 2001, 15, 131–150. [Google Scholar] [CrossRef]
  44. Chaney, T. Distorted Gravity: The Intensive and Extensive Margins of International Trade. Am. Econ. Rev. 2008, 98, 1707–1721. [Google Scholar] [CrossRef]
  45. Huysmans, M.; Noord, D.V. The Market for Lemons from Sorrento and Gouda from Holland: Do Geographical Indications Certify Origin and Quality? USE Working Paper Series; U.S.E. Research Institute: Utrecht, The Netherlands, 2021; Volume 21. [Google Scholar]
  46. Qie, H.; Chen, H.; Lu, Y.; Zhao, X.; Wang, Z. Evaluating the Impact of Agricultural Product Geographical Indication Program on Rural Income: A Case Study of the Yangtze River Delta Region in China. J. Knowl. Econ. 2024. [Google Scholar] [CrossRef]
  47. Bom, P.R.D.; Rachinger, H. A kinked meta-regression model for publication bias correction. Res. Synth. Methods 2019, 10, 497–514. [Google Scholar] [CrossRef] [PubMed]
  48. Ringquiste. Meta-Analysis for Public Management Policy; John Wiley: NewYork, NY, USA, 2013. [Google Scholar]
  49. Hardy, R.J.; Thompson, S.G. Detecting and describing heterogeneity in meta-analysis. Stat. Med. 1998, 17, 841. [Google Scholar] [CrossRef]
  50. Jena, P.R.; Grote, U. Does Geographical Indication (GI) increase producer welfare? A case study of Basmati rice in Northern India. In Proceedings of the ISEE Conference on Advancing Sustainability at the Time of Crisis, Oldenburg–Bremen, Germany, 22–25 August 2010. [Google Scholar]
  51. Gignac, G.E.; Szodorai, E.T. Effect size guidelines for individual differences researchers. Personal. Individ. Differ. 2016, 102, 74–78. [Google Scholar] [CrossRef]
  52. Li, C.; Gao, J.; Ge, L.; Hu, W.; Ban, Q. Do Geographical Indication Products Promote the Growth of the Agricultural Economy? An Empirical Study Based on Meta-Analysis. Sustainability 2023, 15, 14428. [Google Scholar] [CrossRef]
  53. Farinha, D.; Faustino, H.; Nunes, C.; Sales, H.; Pontes, R.; Nunes, J. Bioactive Compounds of Portuguese Fruits with PDO and PGI. Foods 2023, 12, 2994. [Google Scholar] [CrossRef] [PubMed]
  54. Leufkens, D. Eu’s regulation of geographical indications and their effects on trade flows. Ger. J. Agric. Econ. 2017, 66, 223–233. [Google Scholar]
  55. Ma, K.S.K.; Wang, L.T.; Blatz, M.B. Efficacy of adhesive strategies for restorative dentistry: A systematic review and network meta-analysis of double-blind randomized controlled trials over 12 months of follow-up. J. Prosthodont. Res. 2023, 67, 35–44. [Google Scholar] [CrossRef]
  56. Xu, F.; Kong, F.Z.; Peng, H.; Dong, S.F.; Gao, W.Y.; Zhang, G.T. Combing machine learning and elemental profiling for geographical authentication of Chinese Geographical Indication (GI) rice. Npj Sci. Food 2021, 5, 18. [Google Scholar] [CrossRef] [PubMed]
  57. Almeida-Garcia, F.; Lago-Olveira, S.; Rebolledo-Leiva, R.; Gonzalez-Garcia, S.; Teresa Moreira, M.; Ruiz-Nogueiras, B.; Pereira-Lorenzo, S. Growing Triticum aestivum Landraces in Rotation with Lupinus albus and Fallow Reduces Soil Depletion and Minimises the Use of Chemical Fertilisers. Agriculture 2022, 12, 905. [Google Scholar] [CrossRef]
Agriculture 14 00798 g001
Figure 1. Meta-analysis diagram of the relationship between geographical indication products and farmers’ incomes.
Figure 1. Meta-analysis diagram of the relationship between geographical indication products and farmers’ incomes.
Agriculture 14 00798 g001
Agriculture 14 00798 g002
Figure 2. Flowchart of meta-analysis of the relationship between geographical indication products and farmers’ incomes.
Figure 2. Flowchart of meta-analysis of the relationship between geographical indication products and farmers’ incomes.
Agriculture 14 00798 g002
Agriculture 14 00798 g003
Figure 3. Flowchart of literature retrieval, screening, and effect size coding.
Figure 3. Flowchart of literature retrieval, screening, and effect size coding.
Agriculture 14 00798 g003
Table 1. Summary of analyzed articles.
Table 1. Summary of analyzed articles.
No.AuthorsYearMethodIndependent VariableDependent VariableCountry
1Wang Yan2022DIDChilliNet benefits to growersChina
2Rao Huacheng2022Tobit regressionGI ProtectionPoverty incidenceChina
3Liu Peng2022Multiple linear regressionGI ProtectionRural–urban income gapChina
4Chen Chao2021OLSFruitIncome from fruit farmer operationsChina
5Wan Huaqiang2021OLSGI ProtectionFarmers’ per capita incomeChina
6Dong Yaning2021OLSGI ProtectionLevel of growth in agricultural incomeChina
7Chen Xi2020OLSGI ProtectionRural–urban income gapChina
8Ji Xinyu2020OLSGI ProtectionPer capita disposable incomeChina
9Yu Yanli2021Endogenous transformation modelGI ProtectionIncomeChina
10Yang Liuyang2019Linear regressionGI ProtectionCostsChina
11Lu Zhaoyang2018OLSGI ProtectionSolvency of enterprisesChina
12Tai Xiujun2017OLSGI ProtectionFarmers’ per capita incomeChina
13Miao Chenglin2017OLSGI RegistrationsGross agricultural output per capitaChina
14Zhao Jinli2014Joint regression modelGI RegistrationsFarmers’ per capita incomeChina
15Zhao Su2015OLSGI RegistrationsFarmers’ per capita incomeChina
16Liu Huajun2015OLSGI RegistrationsFarmers’ per capita incomeChina
17Zhan Huibing2012OLSGI ProtectionIncomeChina
18Sihui Zhang2023SDMGI RegistrationsUrban–rural income gapChina
19Concetta Cardillo2023OLSGI ProtectionIncomeItaly
20Celso Lopes2022OLSGI RegistrationsIncomePortugal
21Luigi Roselli2016OLSGI ProtectionPrice premiumUSA
22Luigi Roselli2016Price modelCheesePrice premiumFrance
23Wen, Hui2022Multiple regressionGI ProtectionFarmers’ incomeChina
24Daniel HassanTSE2011demand modelsGI ProtectionIncome elasticityUSA
25Pradyot R. Jena2010Random parameter logit (RPL) modelBasmati riceProducer welfareIndia
26Seccia, A2017Non-regression methodsGI ProtectionAgricultural product priceFrance
27Santos, J2005Non-regression methodsGI ProtectionAgricultural product priceBrazil
28Zhang Mier2022Regression methodsGI ProtectionAgricultural product priceChina
29Li Zhaopan2021Non-regression methodsGI ProtectionAgricultural product priceChina
30Yang Liuyang2019Regression methodsGI ProtectionAgricultural product priceChina
31Peng Fung-lan2022Non-regression methodsGI ProtectionAgricultural product priceChina
32Pembebe2019Regression methodsGI ProtectionAgricultural product priceChina
Table 2. Test of publication bias.
Table 2. Test of publication bias.
CategorySample SizeFail-Safe Number
KN
Overall991218
Per capita disposable income423010
Increase in agricultural commodity prices352581
Table 3. Integrity test.
Table 3. Integrity test.
VariableHeterogeneity TestEffects ModelCorrelation Strength
Dfp ValueI2QzVariancePoint EstimationLower LimitUpper Limit
Overall870.00099.8350,181.9202.7801.3170.3480.1040.540High
Per capita disposable income410.00099.9144,541.5502.2701.3490.3890.0560.644High
Increase in agricultural commodity prices340.00999.002094.12011.6400.0040.2550.2140.296Moderate
Table 4. Moderating effect test.
Table 4. Moderating effect test.
VariableCategoryk95%CIHeterogeneity Test
Estimation
Value		Lower LimitUpper LimitQDfp Value
CountryChina640.4120.3040.5091419.130630.000
Other countries240.208−0.1220.49719,441.670230.000
Sampling regionNationwide390.2460.0160.47720,053.990380.000
Region490.4550.3360.5601290.830480.000
Sample typeSpecific GI products280.4000.2590.5251531.410270.000
Total volume of GI products600.3090.0680.51623,163.510590.000
Journal typeJournal130.5620.2780.756396.590120.000
Dissertation750.3100.0620.52143,464.300740.000
Journal qualityHigh110.6300.4690.750736.080100.000
Low640.2380.0230.43220,809.670630.000
Publication yearBefore 2015130.6350.3940.794758.110120.000
2015 and after 2015750.2750.0280.49140,273.560740.000
Research methodMultiple linear regression540.3290.0270.57641,788.620530.000
Others340.3600.2110.492807.390330.000
Data typeSection490.3320.1850.4651133.020480.000
Panel390.3590.0260.62038,458.480380.000
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Li, C.; Ban, Q.; Ge, L.; Qi, L.; Fan, C. The Relationship between Geographical Indication Products and Farmers’ Incomes Based on Meta-Analysis. Agriculture 2024, 14, 798. https://doi.org/10.3390/agriculture14060798

AMA Style

Li C, Ban Q, Ge L, Qi L, Fan C. The Relationship between Geographical Indication Products and Farmers’ Incomes Based on Meta-Analysis. Agriculture. 2024; 14(6):798. https://doi.org/10.3390/agriculture14060798

Chicago/Turabian Style

Li, Chunyan, Qi Ban, Lanqing Ge, Liwen Qi, and Chenchen Fan. 2024. "The Relationship between Geographical Indication Products and Farmers’ Incomes Based on Meta-Analysis" Agriculture 14, no. 6: 798. https://doi.org/10.3390/agriculture14060798

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop