Estimating the Expected Commercial Potential of Saudi Date Exports to Middle Eastern Countries Using the Gravity Model

Abstract

Date production farms account for 10% of total income in the agricultural sector. Although Saudi exports of dates reach many countries, they are still of lower quantity compared to the size of their production. This study investigates the possibility of expanding external marketing of date exports by increasing the marketing efficiency of the existing market, which is expected to lead to increased returns. Therefore, this research uses the gravity model to identify the most critical factors affecting Saudi date exports to Middle Eastern countries. The results indicated the positivity of the per capita GDP in Saudi Arabia, the common border in influencing the increase in date exports, and the opposite effect of membership in the Gulf Cooperation Organization (GCC). In estimating the potential and expected trade capabilities with the Middle Eastern countries, the study results show that the actual value of date exports to the countries of the Middle East represents about 83.37% of its expected potential date trade, and it is possible to increase the export value by 16.63%, or USD 12.75 million. The study provides recommendations to improve date trade further.

1. Introduction

In Saudi Arabia, date production is one of the most important sources of income in the agricultural sector, as it represents about 10% of the total value of agricultural income. On average, the production of dates is more than one and a half million tons annually, produced from about 31 million palm trees. Saudi Arabia ranked second in the world in the production of dates in 2021, with a rate of approximately 16% of the total global production (after Egypt, which produces 18%) [1,2].

Furthermore, Saudi Arabia is one of the largest exporters of dates in the world, accounting for 14% of the total global date exports in 2021. Data from the Saudi General Authority for Statistics [3] indicated an increase in the quantity and value of date exports in 2019 by 13.5% and 14.6%, respectively, compared to 2018. The country exported 184 thousand tons of dates with a value of 865 million Saudi riyals in 2019, compared to 161 thousand tons and 758 million Saudi riyals in 2018. The Gulf Cooperation Council (GCC) countries were the most significant importers of Saudi dates in 2019, with 45%, followed by other Arab countries with 29%, non-Arab Islamic countries with 11.6%, and others with 14.5% [1].

The country can expand external marketing by creating new export opportunities and expanding into existing markets. Increasing the marketing efficiency of Saudi dates will lead to an increase of up to 30% of the agricultural sector’s revenue [4].

In terms of export competitiveness [5,6], the United Arab Emirates, Iraq, Pakistan, Palestine, Tunisia, and Iran demonstrate higher competitiveness in the global date market [7]. Nevertheless, Saudi dates hold a comparative advantage in other markets, such as Africa, Asia, and the Organization of Islamic Cooperation, while being less competitive in the markets of America and Europe. The literature identifies the competitive advantages of marketing Saudi dates both domestically and internationally, pinpointing the most significant determinants through various indicators, including price competition, quantitative competition, market penetration, market share, the extent of export strength, stability, and an index of comparative advantage [8].

Technical, structural, and behavioral challenges exist in marketing [9]. Saudi Arabia’s dates marketing sector deals with significant challenges, such as low-quality marketing services, high costs, and export procedures that must be followed. [9,10]. In addition, the literature analyzed the value chain and marketing opportunities for dates in the GCC countries. The study concluded that among the most prominent issues and obstacles facing the sector in terms of marketing are low quantity and export revenues, inefficient use of by-products, weaknesses in the storage system, and various challenges on the productive side [11]. The study emphasized the importance of developing markets, improving marketing efficiency, raising value-added, and developing secondary products.

Further, some previous studies discuss the ability of competitive dates to be marketed locally and globally. The price factor plays a vital role in marketing dates, as it is considered one of the most critical determinants of the comparative advantage of dates compared to competitors from foreign countries [7,12,13,14].

The exports of Saudi dates have increased during the past ten years (from 70 thousand tons in 2012 to 318 thousand tons in 2021), contributing to the development and advancement of the palm and date sectors in Saudi Arabia. Still, this impact was limited due to the instability of the global market for dates and the movement of the quantity and value of this crop due to competition from other countries. Some of these countries may have greater competitiveness in export operations because of the support they provide, their ability to obtain market information, and the extent to which exporters adhere to international standards.

Previous studies addressed the competitive advantages of marketing Saudi dates locally and internationally, identifying the most critical determinants through various indicators, including price competition, quantitative competition, market penetration, market share, and the extent of export strength and stability. However, it did not address identifying the factors affecting Saudi date exports in light of the regional and spatial ties between them and the economic capabilities of the importing countries. Among the most important determinants are (per capita GDP, geographical distance, common borders, common language, and the membership of the Kingdom and those importing countries in international organizations and bodies). Using the gravity model, we account for these factors to estimate the expected commercial potential for Saudi date exports to countries in the Middle East region.

Therefore, this study aims to determine the influencing factors on Saudi date exports to the countries of the Middle East in the light of the regional and spatial links between them and identify the most important countries that expand or limit their imports of Saudi dates during the period 2000–2019. Additionally, the study aims to estimate the expected commercial potential of Saudi date exporters in those countries. The remainder of this paper comprises three sections. The first section presents the research method and data. The second discusses the results, and the third concludes.

2. Materials and Methods

The research relied on descriptive and quantitative statistical methods in analyzing the data on Saudi Arabia’s dates exports to the countries of the Middle East during the period (2000–2019). We used the gravity (trade flow) model, which mainly depends on panel data (cross-sectional data representing the number of countries and time series representing years for the economic variables of the countries included in the model).

The Gravity model, from the consumption side for dates (DA), assumes a CES utility function for the importer country i.

$$D{A}_{jit}={\left(\frac{{\beta }_{jt}{P}_{jt}{\tau }_{jit}}{P_{it}}\right)}^{1-\sigma }{y}_{it}$$

(1)

$$where the price index P_{it}={\left({\displaystyle \sum }_j{\left({\beta }_{jt}{P}_{jt}{\tau }_{jit}\right)}^{\frac{1}{1-\sigma }}\right)}^{\frac{1}{1-\sigma }}$$

(2)

where ${\beta }_{jt}$ is how much dates in country j are preferred by country i, σ elasticity of substitution between dates (σ > 1), $P_{jt}$ country j export price of dates at time t, pit country i import price, τ transport cost, and y_it nominal income of country i at time t. The importer’s date optimization is subject to a budget constraint, and the summation of the producer’s export of dates must equal the nominal income.

$$y_{it}={\displaystyle \sum }_{i}D{A}_{jit}={\left(B_{jt}{P}_{jt}\right)}^{1-\sigma }{\displaystyle \sum }_i{\left(\frac{{\tau }_{jit}}{P_{it}}\right)}^{1-\sigma }{y}_{it}$$

(3)

Substituting Equation (1), we end with the Gravity dates model:

$$D{A}_{jit}=\frac{y_{jt}{y}_{it}}{y_{wt}}{\left( \frac{{\tau }_{jit}}{P_{jt}{P}_{it}}\right)}^{1-\sigma }$$

(4)

where the $P_{jt}$, $P_{it}$ (price index for country i) are multilateral trade resistance factors and y_wt is world income.

Consequently, we augment the basic gravity model with a population measure per Linne in 1966 and year-fixed and country-pair-fixed effects. Using panel data on 13 countries from 2000 through 2019, our gravity model for determining import and export dates follows [15,16,17]:

$$lnD{A}_{ijt}={\beta }_0+{\beta }_{1}ln{Y}_{it}+{\beta }_{2}ln{Y}_{jt}+{\beta }_{3}lnPO{P}_{it}+{\beta }_{4}lnPO{P}_{jt}-{\beta }_{5}lnDis{t}_{ij}+{\displaystyle \sum }_{j=1}^S{\propto }_{ij}{D}_{ij}+{\gamma }_t+{\epsilon }_{ijt}$$

(5)

where $Y_i \mathrm{and} Y_j$: GDP in two countries i and j,$PO{P}_i \mathrm{and} PO{P}_j$: Number of the population in two countries i and j, $Dis{t}_{ij}$: Distance geographic between two countries i and j, $D_{ij}$: Dummy Variable represents the country pair fixed effects, which control for the invariant characteristic such as (Border—Language—Agreements Commercial … etc.), ${\gamma }_t$ year fixed effects, and ${\epsilon }_{ijt}$ is the error term.

Because the gravity model is a double logarithmic model, the regression coefficients are interpreted as elasticities because the gravity model is double logarithmic. Therefore, we would expect the sign of the elasticities as the economic logic since our relationship hypothesis is positive with the GDP and POP and negative with distance; ${\beta }_1, {\beta }_2, {\beta }_3, {\beta }_4>0 \mathrm{and} {\beta }_5<0$. Since we are interested in estimating a country-specific variable’s effect on trade, we will include exporter-by-importer fixed effects to help us realize the impact of distance, common language, regional trade agreement (RTA), or contiguity. We have a dummy variable to capture the preferential trade agreement membership, showing the treatment group’s average treatment effect with the same characteristics for all covariates except non-membership [17,18].

The final gravity model for the date trade is

$$D{A}_{ij}={\beta }_0+{\beta }_{1}Pc{Y}_{it}+{\beta }_{2}Pc{Y}_{jt}+{\beta }_{3}Dis{t}_{ij}+ex{p}^{\left({\beta }_4{d}_{CB}+{\beta }_5{d}_{GCC}+{\beta }_6{d}_{WTO}+{\beta }_7{d}_{GFT}+{\beta }_8{d}_{lng}\right)}$$

(6)

where: $D{A}_{ij}$ value of country i’s date exports to country j for period t, $Pc{Y}_{it}$ per capita GDP of country i for period t, $Pc{Y}_{jt}$ per capita GDP of country j for period t, And dummy variables such as $d_{CB}$ representing common border, $d_{GCC}$ membership in the (GCC), $d_{WTO}$ membership in the WTO organization, $d_{GFT}$ membership in the Greater Arab Free Trade Area, and $d_{lng}$ is a common language.

Several statistical tests were conducted before estimating the gravity model to find the appropriate model for estimation. We used unit root tests (stability tests) because the lack of stability in the data in estimating the regression models leads to misleading and false results. Despite obtaining good results for some indicators or criteria used in evaluating the validity of the estimated models, one of these indicators is the coefficient of determination. Unit root tests were used for each of the Levin, Lin & Chu in 2002 and the PP-Fisher Chi-square tests in 2001, and the tests were used on each of the study variables by choosing the optimal delay periods according to the AIC standard.

Also, we used a random effect test (RE) and the Breusch-Pagan Test Lagrange multiplier LM. Where the model assumes that the fixed boundary between countries and years is set over time, it reflects the convergence of prices, national income, and other economic and social variables. Where the random effect (RE) and autocorrelation are tested together, the (RE) model is often used because it is characterized by an arbitrary fixed limit that reflects the nature of the different conditions of each country from the other. We used the Hausman Test to find the most suitable model. After the existence of individual peculiarities has been confirmed, meaning that each country has its specificity, the next step is to know the quality and nature of these peculiarities, meaning whether these peculiarities are of the type of fixed effects or of random effects, i.e., the choice between a fixed effects model and a model with random effects to determine the final appropriate model for study inputs [19].

A Method of Estimating the Expected or Potential Trade Potential

The trading capabilities of a country are calculated by the following steps:

• Calculate the estimated exports ${\widehat{EX}}_{ij}$ between country i (Saudi Arabia) and country j (Middle East) during period t from the estimated gravity model.
• Calculate Adjusted Estimated Exports ($E{X}_{ijt}^{*}$) according to the following equation:

  $$E{X}_{ijt}^{*}=\frac{{\widehat{EX}}_{ij}\left({{\displaystyle \sum }}_{j}E{X}_{ijt}-E{X}_{ijt}\right)}{\left({{\displaystyle \sum }}_j{\widehat{EX}}_{ijt}-{\widehat{EX}}_{ijt}\right)}$$

  (7)

  where $E{X}_{ijt}$ represents the actual exports between countries i and j during the time period t.
• Calculating the trade potential ($P{C}_{ijt}$) for a certain period as the arithmetic average of estimated exports and adjusted estimated exports:

  $$P{C}_{ijt}=\frac{{\widehat{EX}}_{ijt}+E{X}_{ijt}^{*}}{2}$$

  (8)

Accordingly, the US Department of Agriculture (USDA) database calculates the trade of dates in Middle Eastern countries. Then, the study estimates the gravity model during the study period from 2000 to 2019. The countries of the Middle East, in particular, as shown on the website of the USDA, are numbered 15 countries, and they are as follows: Saudi Arabia, the United Arab Emirates (UAE), Turkey, Iraq, Iran, Israel, Kuwait, Jordan, Yemen, Oman, Lebanon, Qatar, Syria, Bahrain, and the West Bank. Import and export data for Saudi Arabia’s date’s trade were collected from the Saudi Arabia General Authority for Statistics (GASTAT), the Food and Agriculture Organization (FAOSTAT), and the US Department of Agriculture (USDA), as well as reports published by the National Center for Palms and Dates.

3. Results

Table 1. Statistical summary of the value of Saudi dates exported to countries in the Middle East and the most important economic variables for Saudi Arabia and importing countries during the period (2000–2019).

Scale	Saudi Date Exports to the Middle East (USD 1000)	Saudi Arabia’s GDP Per Capita (USD 1000)	Saudi GDP (Million USD)	GDP of Importing Countries (Million USD)	The Importing Country’s GDP Per Capita (USD 1000)	Saudi Population (Million)	Importing Country’s Population (Million)	Geographical Distance between Saudi Arabia and Importing Countries (km)
	dAij	$\mathit{P}\mathit{c}{\mathit{Y}}_{\mathit{i}}$	Yi	Yj	$\mathit{P}\mathit{c}{\mathit{Y}}_{\mathit{j}}$	POPi	POPj	DIST
Average	5995.6	17.73	505,686	129,528.95	17.91	27.32	13.36	1316.5
Max	65,925	25.24	792,967	957,783.02	85.08	34.27	83.43	2528.4
Min	0.001	8.68	184,137	3555.8	0.55	20.66	0.59	674.7
Standard deviation	8706.9	5.71	218,275	202,294.6	19.47	4.33	20.10	553.37

Source: FAOSTAT (2022), the National Center for Palms and Dates (NCPD), the Arab Organization for Agricultural Development (AOAD), Distance Calculator, and World Bank website.

shows the statistical summary of the study variables. The Saudi maximum gross domestic product (GDP) through the study period (2000–2019) was 792.97 billion USD, whereas the lowest value was about 184.14 billion USD in 2001. The largest GDP value for Middle Eastern countries during the study period was 957.78 billion USD in 2012 for Turkey, while the lowest value was about 3.56 billion USD for Palestine in 2002. For the per capita value, Saudi Arabia achieved the highest value during the study period in 2011 by 25.24 thousand USD, while the lowest value for the same country was 8.68 thousand USD in 2001. For the per capita GDP of other countries in the Middle East, we found the largest value was 85.08 thousand USD in 2013 for Qatar, while the lowest per capita GDP was 0.55 thousand USD in Yemen in 2001 [20].

The geographical distance between Saudi Arabia and those countries Importing Saudi dates in the Middle East is between 2528.4 km for Turkey and 674.7 km for Bahrain [21].

The results of the unit root test show the significant effect of (t) values calculated for both tests of the study variables used in estimating the gravity model of Saudi dates exports to the countries of the Middle East under study, which indicates that these variables are stable in each country over study time. That is, the null hypothesis is rejected, and the alternative hypothesis, which is that the variables are stationary and stable over time, is accepted in

Table 2. Results of unit root tests for study variables.

Variables	Method	t-STATISTIC	Prob.	Cross-Sections	Obs	Lags
LnDAIJ	Levin, Lin & Chu t	−1.71670	0.0430 **	11	198	1
	PP—Fisher Chi-square	49.8182	0.0006 ***	11	198	1
LnYi	Levin, Lin & Chu t	−7.05284	0.0000 ***	11	187	2
	PP—Fisher Chi-square	55.6678	0.0001 ***	11	187	2
LnYj	Levin, Lin & Chu t	−6.05008	0.0000 ***	11	187	2
	PP—Fisher Chi-square	63.5727	0.0000 ***	11	187	2
LnPOPi	Levin, Lin & Chu t	−14.9262	0.0000 ***	11	198	1
	PP—Fisher Chi-square	44.1686	0.0034 ***	11	198	1
LnPOPj	Levin, Lin & Chu t	−4.83050	0.0000 ***	11	198	1
	PP—Fisher Chi-square	32.2839	0.0727 **	11	198	1
ln$\mathit{P}\mathit{c}{\mathit{Y}}_{\mathit{i}}$	Levin, Lin & Chu t	−4.48272	0.0000 ***	11	198	1
	PP—Fisher Chi-square	27.3879	0.1969	11	198	1
ln$\mathit{P}\mathit{c}{\mathit{Y}}_{\mathit{j}}$	Levin, Lin & Chu t	−6.39049	0.0000 ***	11	187	2
	PP—Fisher Chi-square	53.9406	0.0002 ***	11	187	2

Null: Unit root (assumes common unit root process). ** significant at 5 *** significant at 10% Source: compiled and calculated from the data in Table 1.

.

The results of the statistical significance of the LM RE Breusch Pagan Test indicate the rejection of the null hypothesis that the fixed term between countries and years is not constant over time, in addition to rejecting the hypothesis of no autocorrelation.

The results of the Hausman Test indicate that the Chi-Sq. statistic equals 3.884 and the p-value equals 0.143, greater than the significance level of 0.05. Therefore, we cannot reject the null hypothesis and that the “Random Effect Model” is the appropriate model for the study variables, and this is logical for the different circumstances from one country to another [17].

3.1. Estimation of the Gravity Model for Saudi Date Exports to the Countries of the Middle East

After conducting static tests and homogeneity and determination tests, which aim to determine the appropriate model for the data and inputs of the study, the existence of individual effects is confirmed, meaning that each country importing Saudi dates from the countries of the Middle East has its advantages and specificities. The Husman test, which looks at the nature of these individual effects, concludes that these particular effects have a random nature. Therefore, the appropriate model for the data and inputs of the study is the random individual effects model, as shown in

Table 3. Results of estimating the gravity model for Saudi date exports to the Middle East countries during the period (2000–2019).

Variable	Coefficient	Std. Error	t-Statistic	Prob.
C	−17.05	8.06	−2.11	0.05
$\mathrm{Ln}(\mathit{P}\mathit{c}{\mathit{Y}}_{\mathit{i}}$)	1.85	0.23	8.14	0.00
$\mathrm{Ln}(\mathit{P}\mathit{c}{\mathit{Y}}_{\mathit{j}}$)	0.73	0.21	3.41	0.00
Ln(DISTij)	−0.02	1.17	−0.02	0.99
${\mathit{d}}_{\mathit{C}\mathit{B}}$	2.81	1.35	2.08	0.04
${\mathit{d}}_{\mathit{G}\mathit{C}\mathit{C}}$	−3.32	1.00	−3.31	0.00
${\mathit{d}}_{\mathit{W}\mathit{T}\mathit{O}}$	0.67	1.10	0.61	0.54
R-squared	0.52		Root MSE	0.88
Adjusted R-squared	0.51		Mean dependent var	1.86
S.E. of regression	0.89		S.D. dependent var	1.25
F-statistic	33.42		Sum squared resid	149.84
Prob(F-statistic)	0.00		Durbin−Watson stat	1.79
Individual effects of countries
UAE	BHR	JOR	KWT	LBN
1.374	−0.591	−0.584	0.395	1.594
OMN	PSE	QAT	SYR	TUR
−1.160	−2.017	−0.018	0.423	0.0001
YEM
0.584

Source: compiled and calculated from the data in Table 1 and Table 2.

, which represents the gravity model of Saudi date exports to countries in the region (2000–2019).

The results of the estimated model show that per capita GDP of Saudi Arabia ($Pc{Y}_i$), per capita GDP of other countries ($Pc{Y}_j$), distance geographic between Saudi Arabia and other imported countries (DISTij), common border ($d_{CB}$), membership in the Gulf Cooperation Organization (GCC) ($d_{GCC}$), and membership in the WTO organization ($d_{WTO}$) explain about 51% of the changes that occur in Saudi exports of dates to those countries according to the value of the adjusted coefficient of determination (adjusted R2). The rest of the variables that are not explained by the model could be due to factors not included in the model, and they have been excluded, such as the common language variable ($d_{lng}$), joining the importing countries to the Greater Arab Free Trade Area variable ($d_{GFT}$), and the GDP of importing countries, and the population of Saudi Arabia and the importing countries, because these variables cause the problem of multiple linear correlation. In addition to the proof of the overall statistical significance of the model according to Fisher’s test, which leads to the rejection of the null hypothesis and acceptance of the alternative hypothesis that the model coefficients differ from zero, this confirms the overall significance of the model. The value of the DW test indicates that the model is free from the problem of autocorrelation errors.

Table 3 shows the results of estimating the gravity model for Saudi date exports to Middle Eastern countries during the period 2000–2019. It is clear that the signs of the parameters of the economic variables are identical to the economic logic, represented by the per capita share of the value of the gross domestic product, whether for Saudi Arabia or the importing countries, as well as the non-economic variables represented by the geographical distance variable and the dummy variables defined by ($d_{CB}$), ($d_{WTO}$), while the sign of the dummy variable differed for the variable ($d_{GCC}$). It also showed that all variables in the model were statistically significant, except for the variable’s geographical distance and $d_{WTO}$.

As the results of the estimation in Table 3 show, an increase in per capita GDP in Saudi Arabia of 1% leads to an increase in its exports of dates to the countries of the Middle East of 1.85%, and an increase in per capita GDP in the importing countries under study of 1% leads to an increase in Saudi exports of dates to the countries of the Middle East of 0.73%. The reason for the opposite effect of the geographical distance is that the increase in geographical distance will lead to an increase in transportation costs.

By measuring the impact of the countries of the Middle East on the permeability of Saudi date exports to their markets, the results of the gravity model for Saudi date exports indicate that the impact of these countries on Saudi date exports is different from one country to another, whether in terms of value or sign Table 3. It is clear that the countries responsible for increasing date exports from Saudi Arabia are the United Arab Emirates, Kuwait, Lebanon, Syria, and Yemen, which contributed to the increase in Saudi date exports by 1.37%, 0.39%, 1.59%, 0.42%, and 0.58%, respectively. While the countries responsible for the decline of Saudi dates are Bahrain, Jordan, Oman, Palestine, and Qatar, they contributed to the decline in date exports by 0.59%, 0.58%, 1.16%, 2.02%, and 0.02%, respectively. The reason for this may be due to the proximity of some of those countries to other countries competing with Saudi Arabia in those markets, such as the Emirates and Kuwait, which are close to the countries of Bahrain, Qatar, and Oman. Accordingly, it is necessary to work on finding ways to reduce transportation costs with those countries and to develop and increase the exports of Saudi dates to all Middle Eastern countries in general and the GCC countries in particular.

3.2. Estimating the Potential and Expected Trade Capabilities of Saudi Arabia with the Countries of the Middle East Region

According to the results of

Table 4. Estimate the expected commercial potential of Saudi date exports to Middle Eastern countries during the study period.

Importing Country	Average Actual Exports		Potential (Expected) Commercial Capabilities USD 1000	%Actual Exports of Trade Capacity
	USD 1000	%
UAE	19,642.36	30.73	13,310.03	147.58
Bahrain	1277.95	2.00	2923.529	43.71
Jordan	8202.25	12.83	20,983.38	39.09
Kuwait	7778.35	12.17	7366.419	105.59
Lebanon	4873.55	7.62	3278.947	148.63
Oman	2216.403	3.47	3144.826	70.48
Palestine	126.5556	0.20	458.133	27.62
Qatar	4102.85	6.42	7216.541	56.85
Syria	1081.092	1.69	1038.837	104.07
Turkey	3793.55	5.93	4018.264	94.41
Yemen	10,826.4	16.94	12,932.99	83.71
total	63,921.31	100	76671.9	83.37

Source: calculated from the results of the estimated model in Table 3.

, the actual value of Saudi date exports to the countries of the Middle East represents about 83.37% of their expected potential, which means that there is a chance to increase Saudi Arabia’s commercial capabilities in some of those countries. Therefore, those countries could be targeted to increase Saudi date exports. According to the result, the value of exports could be increased from 63.92 million USD to 76.67 million USD. The value of dates exported to the UAE represented about 30.73% of the average value of Saudi date exports during the study period, and the actual value of its exports far exceeded the expected value in the UAE market. Among the markets that achieved an outperformance of their actual exports over their potential are Kuwait, Lebanon, and Syria by 105.59%, 148.63%, and 104.07%, respectively. Countries that are almost achieving their potential or expected trade potential are Turkey, Yemen, and Oman, where the values of their actual imports of Saudi dates are 94.41%, 83.71%, and 70.48%, respectively.

There is also another group of countries in which the actual value of Saudi date exports is below the potential value, such as Bahrain, Jordan, Palestine, and Qatar, where such values represent only 43.71%, 39.09%, 27.62%, and 56.85% of the value of their potential, respectively, meaning that the exchange process of the trade of Saudi dates with those countries is not enough.

Overall, there is significant commercial potential for Saudi date exports within the countries of the Middle East by increasing the value of Saudi date exports to the optimal level of potential, which leads to an increase in the value of Saudi date exports by about 16.63% of their current value. In other words, increasing Saudi date exports to the optimal level is expected to increase Saudi date exports by USD 12.75 million.

4. Conclusions

Saudi Arabia is one of the largest exporters of dates in the world. The average value of Saudi date exports to Middle Eastern countries was about 5995.6 thousand USD during the study period 2000–2019. The GCC countries are among the most important importing countries for Saudi dates, accounting for 45% of the total export, followed by other Arab countries at 29%, and then other non-Arab Islamic countries at 11.6%. Saudi Arabia competes with other countries in producing and exporting dates, as some countries have greater competitiveness in export operations.

This research aims to examine the potential to enhance the exports of Saudi dates to the countries of the Middle East, considering the regional and spatial links, by identifying the most important factors affecting the exports of Saudi dates to those countries and the most important ones that are expanding or limiting their imports of Saudi dates during the period 2000–2019. As well as estimating the expected commercial potential of the Saudi date exporters in those countries using the gravity model. The most important results of the estimated model are represented by the positive effect of the per capita value of the GDP in Saudi Arabia and the Middle East on Saudi Arabia exports to those countries. The study results also indicated a direct relationship between the exports of Saudi Arabian dates and the variable representing the common borders, while the results indicated the existence of an inverse relationship with the variable representing the affiliation of those countries to the GCC.

On the aspect of estimating the expected trade capabilities of Saudi Arabia with the countries of the Middle East region, the actual value of Saudi date exports to the countries of the Middle East region represents about 83.37% of the level of its expected potential, which means that there are high commercial capabilities of Saudi Arabia in some of those countries, but they are not exploited. The research identified those countries to increase exports of Saudi dates to them so that the value of exports could be increased from 63.92 million USD to 76.67 million USD, including a group of countries that are close to achieving their potential or expected trade potential, namely Turkey, Yemen, and Oman. There is another group of countries in which the actual value of Saudi date exports fell below the potential value, including Bahrain, Jordan, Palestine, and Qatar, meaning that the process of trade exchange for Saudi dates with those countries is not sufficient. Evidence illustrates that there is significant commercial potential for Saudi date exports within the countries of the Middle East, where it is possible to increase the value of Saudi exports of dates to the optimum level of potential to increase the value of Saudi date exports by 16.63% of their current value, or USD12.75 million.

Based on the foregoing results, the study recommends focusing on the most important factors activating the foreign trade sector, which are expected to contribute to the development and increase in Saudi date exports in particular. Finally, the study suggests developing future trade policies that focus on countries that have not fully exploited their markets and in which actual exports have decreased from what was expected, such as Turkey, Yemen, Oman, Bahrain, Jordan, Palestine, and Qatar. Focusing on those markets will lead to an increase in the value of Saudi date exports by about USD12.75 million.

The limitations of our study are two-fold. First, the model uses data before the COVID-19 pandemic, while agricultural trade might not be the same post-pandemic. Second, the model did not account for trade barriers or economic and political instability within potential countries, according to expert Saudi date.

The palms and dates sector holds immense economic, social, and environmental significance, playing a crucial role in achieving sustainable agricultural and rural development in Saudi Arabia. However, the sector remains largely traditional in its practices, necessitating a transformative shift towards advanced processes. This entails seamlessly linking production with manufacturing and marketing to enhance competitiveness and secure greater returns. Saudi Arabia’s Vision 2030 clearly prioritizes the development and sustainability of the palm and date sector. Several dedicated programs aim to boost its contribution to the national economy. These efforts emphasize effective collaboration between government agencies, research institutions, universities, farmers, and the private sector to develop value chains, improve the quality and quantity of production, reduce waste, raise the efficiency of marketing dates, encourage investment, provide the necessary information, data, and studies, improve the efficiency of the supply chain, and enhance human and institutional capabilities [22].

Expanding Saudi date exports aligns with sustainable development goals. It fuels economic growth, boosts benefits for domestic production through increased returns and reduced production losses, fosters rural stability, and contributes to food security in importing countries.