metadata: authors: 0: author: Arezki,Rabah
1: author: Belmejdoub,Oussama
2: author: Diab,Bilal
3: author: Kalla,Samira
4: author: Ha Nguyen
5: author: Saif,Abdulla Fahed Abdulla Ali
6: author: Yotzov,Ivan Victorov
count: Middle East and North Africa
docna: 0: docna: From #Hashtags to Legislation : Engagement
            and Support for Economic Reforms in the Gulf Cooperation
            Council Countries
docty: Policy Research Working Paper
bdmdt: 2022-06-15T00:00:00Z
abstracts: cdata!: Ownership of reforms by citizens is
            often presented as important for success. This paper
            explores media engagement and support for economic reforms
            in the Gulf Cooperation Council countries using text
            analysis techniques on publicly available sources. The
            results show that while reform efforts have intensified in
            recent years in the Gulf Cooperation Council countries,
            these efforts tend to focus on stronger rather than weaker
            policy areas, potentially limiting the growth-enhancing
            effect of reforms. Social media analysis using Twitter shows
            that the population's support for reforms has been
            declining. The analysis of traditional news media points to
            more engagement by international than by local media.
            However, sentiment from international media is less positive
            about economic reforms in the Gulf Cooperation Council
            countries. Sentiment in international media and social media
            matters, as evidenced by its positive and strong correlation
            with foreign direct investment inflows into the Gulf
            Cooperation Council countries.
display_title: From #Hashtags to Legislation :
            Engagement and Support for Economic Reforms in the Gulf
            Cooperation Council Countries
closedt: 2022-06-15T00:00:00Z
listing_relative_url: /research/2022/06/33843497/hashtags-legislation-engagement-support-economic-reforms-gulf-cooperation-council-countries
topicv3: Sector and Policy Regulatory Reforms
            m1504631 3133,Citizen Engagement for Social Protection
            and Labor m1582975 4452
publishtoextweb_dt: 2022-06-15T00:00:00Z
dois: 10.1596/1813-9450-10090
origu: Off of Sr VP Dev Econ/Chief Econ (DECVP)
author_keys: 0: author_key: 1596791
1: author_key: NA
2: author_key: NA
3: author_key: 1922434
4: author_key: NA
5: author_key: 1912192
6: author_key: 1670614
model_extractions: Policy Research Working Paper 10090

# From #Hashtags to Legislation

Engagement and Support for Economic Reforms in the Gulf Cooperation Council Countries _Rabah Arezki Oussama Belmejdoub Bilal Diab Samira Kalla Ha Nguyen Abdulla Saif Ivan Yotzov_ Middle East and North Africa Region Office of the Chief Economist June 2022
Policy Research Working Paper 10090

# **Abstract**

Ownership of reforms by citizens is often presented as important for success. This paper explores media engagement and support for economic reforms in the Gulf Cooperation Council countries using text analysis techniques on publicly available sources. The results show that while reform efforts have intensified in recent years in the Gulf Cooperation Council countries, these efforts tend to focus on stronger rather than weaker policy areas, potentially limiting the growth-enhancing effect of reforms. Social media analysis using Twitter shows that the population’s support for reforms has been declining. The analysis of traditional news media points to more engagement by international than by local media. However, sentiment from international media is less positive about economic reforms in the Gulf Cooperation Council countries. Sentiment in international media and social media matters, as evidenced by its positive and strong correlation with foreign direct investment inflows into the Gulf Cooperation Council countries.

This paper is a product of the Office of the Chief Economist, Middle East and North Africa Region. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at hanguyen@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# **From #Hashtags to Legislation: Engagement and Support for Economic Reforms in the Gulf Cooperation Council Countries**

Rabah Arezki, Oussama Belmejdoub, Bilal Diab, Samira Kalla, Ha Nguyen, Abdulla Saif, and Ivan Yotzov<sup>1</sup> Keywords: Economic Reforms, Sentiment, Ownership, Engagement, Social Media, News Media, Gulf Cooperation Council countries JEL Codes P41; N25; D7 1Rabah Arezki is a Senior Fellow at Harvard University, Oussama Belmejdoub is Lead Data Scientist at Quantcube Technology, Bilal Diab is a Data Scientist at Artefact, Samira Kalla is an Economist at Deutsche Bank, Ha Nguyen is a Senior Economist at the World Bank’s Chief Economist Office for the Middle East and North Africa, Abdulla Saif is at Abu Dhabi’s Supreme Council for Financial and Economic Affairs, and Ivan Yotzov is a PhD candidate at the University of Warwick. We are grateful to Merza Hussain Hasan, Abdulmuhsen Saad Alkhalaf, Issam Abousleiman, Roberta Gatti, Daniel Lederman, Paul Moreno-Lopez, Ismail Radwan, and Thanh-Long Huynh for valuable inputs. We thank Kevin Carey, Shantayanan Devarajan, Stuti Khemani, Roy Van der Weide, Sona Varma, Khaled Alhmoud, Shahd Sulaiman A Alhamdan, Jaime de Pinies Bianchi, Sameh El-Saharty, Manju Haththotuwa, Bob Beschel, Ali Halawi, Aminur Rahman, Tarek Masoud and participants at the workshop “Frontier in Big Data Analyses on Economic Reforms: The Case of the Gulf Cooperation Council Countries” and at the presentation to the The Kingdom of Saudi Arabia's National Center for Performance Management (ADAA) for helpful comments and suggestions.

**_<mark>Disclaimer:</mark>_** _<mark>The findings, interpretations, and conclusions expressed in this paper are of the authors and do not necessarily reflect the views of the World Bank, the Executive Directors of the World Bank or the governments they represent. The World Bank does not guarantee the accuracy of the data included in this work.</mark>_
# I. Introduction

Before the pandemic, growth in the Middle East and North Africa region (MENA) recorded a noticeable slowdown due to structural barriers and shocks. The region experienced a systematic slowdown in growth, with the average growth rate declining from 4.6% between 2000 and 2009 to 3% between 2010 and 2019. As a result, most MENA countries lagged behind their income peers in growth in income per capita over the last two decades (Arezki et al., 2020a). In addition, the region has shown considerable heterogeneity in economic growth across countries. Most notably, developing oil exporters witnessed negative growth before the pandemic. The protracted low-growth performance has been caused by external shocks (e.g., sluggish global growth, falling oil prices), domestic shocks, and structural impediments to growth. Therefore, economic reforms will be crucial to restoring growth, especially after the Covid-19 crisis.

In recent years, the GCC countries - Saudi Arabia, United Arab Emirates, Kuwait, Oman, Bahrain, and Qatar- have engaged in profound economic reforms (IMF 2016, World Bank 2018). From initial reforms such as spending restraints, efforts are moving to deeper reforms, such as rolling back costly and distortionary energy subsidies, increasing revenues from the non-oil sector, implementing business environment and labor reforms, and public financial management reforms (World Bank 2018). Efforts to understand and support economic reforms in the GCC are much needed.

A key component in ensuring the sustainability of economic reforms is broad participation, engagement, and support for the economic reform process by the population and other domestic and international stakeholders. Broad participation in economic policies could bring many benefits. Broad participation and public deliberation have the potential to aggregate preferences and reshape them through dialogue and argumentation (World Bank, 2017). Examining these norms and preferences and how they evolve is key to understanding why conflicts of interest persist and how reformers can find common ground for socially beneficial reforms (Khemani, 2020). Broad participation and engagement could also increase the contestability of policy ideas. Consequently, reforms could be of higher quality, and efforts could be focused on the most-needed reforms. Available empirical evidence shows that citizen engagement largely improves outcomes at the local level (Baiocchi, 2005; World Bank, 2017). Citizen support can also be instrumental in improving the legitimacy of decisions. The Arab Spring is a powerful reminder of the importance of inclusiveness and public support.

Little has been done to analyze the engagement and support for economic reforms<sup>2</sup> in the GCC. This paper is an effort to fill in the needed gap using novel data from news and social media. The paper contributes to the existing literature on economic reforms, which has typically focused only on the effects of implemented reforms (see Prati et al., 2013, Alesina et al., 2020).

The paper uses text analysis techniques on publicly available big data sources: passed laws and decrees, social media, and news media. The use of data from newspapers and social media platforms has several advantages. They can be real-time and cover many countries. They can provide more granular and

> 2 Economic reforms are understood as changes introduced with the intention to improve the economy. For example, we do not examine political reforms in this paper.

2
insightful analyses that are not possible with traditional economic reform data or surveys.<sup>3</sup> For example, the paper measures engagement in economic reforms by constructing the share of news articles that discuss economic reforms. Sections III and IV discuss this in detail.

The remainder of the paper is organized as follows: Section II takes stock of the GCC's past and current economic reforms. It constructs a novel data set of passed laws and decrees by web-scraping national legislative archives from 1980 to 2019. Section III uses tweets in Arabic and text analysis techniques to understand the population's engagement and support for economic reforms. Section IV provides a similar analysis using a large data set of newspaper articles on economic reforms in English and Arabic. Finally, Section V concludes.

Section II reveals that reform efforts have intensified in recent years. The number of laws and decrees passed in the GCC has been quickly rising, driven partly by GCC countries’ efforts to diversify their economies. However, these nations tend to pass more laws and decrees in stronger than weaker policy areas, indicating that reforms do not address lagging policy areas.

Section III documents increasing engagement but declining support for economic reforms from the population in recent years. The number of engaged users who tweet about economic reforms has increased in recent years. In addition, the number of economic reform tweets per engaged user has been rising dramatically. However, the sentiment of economic reform tweets is worsening, suggesting either growing discontent about the current economic situation or shrinking support for the current direction of economic reforms.

Section IV shows that international media is more engaged in economic reform discussions in the GCC countries than local media (and potentially domestic participants, more broadly). In addition, international media is more critical of the GCC’s current economic situation or the directions of current economic reforms compared with local media. Sentiment from international media matters because it is correlated with FDI inflows into the GCC.

# II. Taking Stock of Economic Reforms in the GCC

This section takes stock of the implemented economic reforms in the GCC because their content and focus could impact engagement and support from the population and other stakeholders. The objective is to understand whether these reforms are geared towards lagging policy areas. In doing so, a novel database of laws and decrees passed by the GCC countries is constructed. Data are obtained by web-scraping countries’ national legislative archives (see Appendix A1 for the details). All recorded laws and decrees from 1980 to 2019 are collected for each country. Each downloaded legislation has a title, source, and date of the legislation.<sup>4</sup>

## II.1 A Novel Database of Laws and Decrees in the GCC

Since we focus on economic reforms, we map the extracted laws and decrees to ten economic policy

> 3 For example, the Arab Barometer (https://www.arabbarometer.org/) surveys people’s view about current economic conditions among other issues in the MENA region. This is a related, but narrower, approach. GCC countries are not typically covered in the Arab Barometer. For example, only Kuwait was covered in the Fifth Wave (2018-2019).

> 4 Since many laws are in unpassable pdf or image format, we did not obtain the full content of all laws. This is left for future research.

3
pillars from the World Economic Forum's (WEF) Global Competitiveness Indices (GCI) and export diversification from the United Nations Conference on Trade and Development (UNCTAD).<sup>5</sup> The mapping process was conducted using keyword searches in the titles of extracted laws and decrees.<sup>6</sup> To the best of our knowledge, this presents the first comprehensive data set covering all GCC reforms passed from 1980 to 2019 by policy pillar (see Appendix A1 for a detailed explanation).

The number of passed laws and decrees has increased rapidly across the GCC countries in the last few years (see Figure II.1), reflecting intensifying reform efforts. Among the policy pillars, “Diversification” contributes most significantly to the increase in many countries (see Figure A1.2 in Appendix A1).

**Figure II.1: Total Number of Laws and Decrees in the GCC countries – 1980-2019**

<!-- Start of picture text --> 700<br>600<br>500<br>400<br>300<br>200<br>100<br>0<br>Year<br>Bahrain Kuwait Oman<br>Qatar Saudi Arabia UAE<br>1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020<br>Number of Laws and Decrees<br><!-- End of picture text -->

# II.2 Do Economic Reforms in the GCC Focus on Lagging Policy Areas?

We examine whether the GCC countries implement reforms in lagging policy areas, as measured by the World Economic Forum's (WEF) Global Competitiveness Indices (GCI) and the United Nations Conference on Trade and Development (UNCTAD)’s Export Diversification. We construct a "Distance to Policy Frontier” measure for each GCC country and policy pillar. A higher score implies that the country is further away from the policy frontier, based on the ranking of WEF’s GCI and UNCTAD (see Appendix A2 for details).

Figure II.2 presents scatterplots between the Number of Laws and Decrees passed versus lagged Distance to Policy Frontier (i.e., the distance to policy frontier _in the previous year_ ) between 2008 and 2018. The figures reveal that the GCC countries passed more laws and decrees in policy areas closer to the policy frontiers. In other words, economic reforms in the GCC do not focus on lagging policy areas, at least in terms of quantity. This finding is true for all countries except Saudi Arabia. “Innovation” and “Technology

> 5 The final eleven policy pillars are as follows: Institutions; Infrastructure; Macroeconomic Environment; Health and Primary Education; Higher Education and Training; Goods Market Efficiency; Labor Market Efficiency; Financial Market Development; Technological Readiness; Innovation; and Export Diversification.

> 6 Note that many laws and decrees are not mapped to any policy pillar (see Appendix A1).

4
Readiness” are two important lagging policy areas that have relatively few numbers of laws and decrees. In contrast, “Diversification”, also a lagging policy area, has received more laws and decrees. We test this hypothesis formally in Appendix A2 with different econometric specifications and confirm the robustness of this finding.

One possible explanation for the finding is that countries enter a 'virtuous cycle' whereby they have more capacity to implement reforms in areas of pre-existing strength. Another argument is related to the sequencing of reforms. The ‘right’ reforms are not necessarily on weak policy areas but the most logical next step (Edwards, 2009; <mark>Feltenstein and Nsouli, 2003</mark> ). More studies and thoughtful debates are needed to understand the countries’ current reform efforts. They will likely help policy makers boost the engagement and support for economic reforms, which we will discuss in the next section.

**Figure II.2: Number of Laws and Decrees Passed and Lagged of Distance to Policy Frontier**

<!-- Start of picture text --> Bahrain Kuwait Oman<br>Qatar Saudi Arabia UAE<br>0 20 40 60 80 0 20 40 60 80 0 20 40 60 80<br>Distance to Frontier, Lagged (100: farthest away from the frontier)<br>Diversification Financial Market Development Goods Market Efficiency Health and Primary Education<br>Higher Education and Training Infrastructure Innovation Institutions<br>Labor Market Efficiency Macroeconomic Environment Technological Readiness<br>150<br>100<br>50<br>0<br>150<br>100<br>50<br>0<br>Number of Laws and Decrees Passed<br><!-- End of picture text --> _Note_ : A higher ‘Distance to Policy Frontier’ implies being farther away from policy best practices. GCI data are from 2007 to 2017 due to data constraints from WEF’s GCI database (the GCI scores are only methodically consistent and comparable across years during this period).

5
The number of the laws and decrees might not capture the most important laws and decrees. In other words, it might not reflect the depth and significance of economic reforms. We use news media to provide a robustness check by focusing on reform announcements in the press. The argument is that media chatter about reform announcements can pick up reforms that are perceived as important. Similar results are obtained when reform announcements are used instead of the number of laws and decrees. Figure II.3 shows scatterplots between the reform announcements about a policy pillar versus its lagged Distance to Policy Frontier (i.e., the distance to the policy frontier _in the previous year_ ) between 2007 and 2017. A policy pillar’s lagged distance to the frontier is not significantly correlated to reform announcements (see Appendix A2 for more detail).

## **Figure II.3: Number of Laws and Decrees Passed and Reform Announcements**

<!-- Start of picture text --> Bahrain Kuwait Oman<br>Qatar Saudi Arabia UAE<br>0 20 40 60 80 0 20 40 60 80 0 20 40 60 80<br>Distance to Frontier, Lagged (100: farthest away from the frontier)<br>Diversification Financial Market Development Goods Market Efficiency Health and Primary Education<br>Higher Education and Training Infrastructure Innovation Institutions<br>Labor Market Efficiency Macroeconomic Environment Technological Readiness<br>2<br>1.5<br>1<br>.5<br>0<br>2<br>1.5<br>1<br>Reform Announcements Index .5<br>0<br><!-- End of picture text --> _Note_ : A higher ‘Distance to Policy Frontier’ implies being farther away from policy best practices. GCI data are from 2007 to 2017 due to data constraints from WEF’s GCI database (the GCI scores are only methodically consistent and comparable across years during this period).

# III. Population’s Engagement and Support for Economic Reforms: Insights from Social Media

Drawing insights from social media, this section examines the people's engagement and support for current economic reforms in the GCC. As demonstrated by the long-lasting consequences of the Arab Spring, this aspect is critical for the long-term sustainability of economic reforms. Our thesis is that social media can reflect the population’s true sentiment toward economic reforms. To our best knowledge, this paper is the first systematic effort to shed light on the general attitude towards economic reforms in the GCC countries.

6
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violent activities (Besley et al., 2019), and public support for foreign military interventions (Fetzer et al., 2021). Our paper focuses on news media coverage and sentiment about economic reforms in the GCC.

We use newspaper data from the Dow Jones News Snapshot API. This global news database provides access to newspaper articles from thousands of sources in 28 languages. In addition to the full text, it also includes tags for each document, which identify the following: (i) country or countries discussed in the article, (ii) the country of origin of the newspaper, and (iii) the subject(s) of the articles. For this paper, we carefully select articles in the 28 languages which contain terms relating to "economy" and "reforms" for each of the six GCC countries (see Appendix A4). Our methodology yields 138,782 articles that are tagged to one or more of the six GCC countries. Of these, 46% are in English, 39% are in Arabic, and the remaining 15% are in 26 other languages. Therefore, this paper focuses on English and Arabic media.

# IV.1 Engagement in Discussions on Economic Reform the from News Media

We begin by analyzing the evolution of reform coverage across the GCC countries. We find that the number of economic reform articles varies significantly over time and across countries. To address this, we create an index for each country that captures _the percentage of all news articles that discuss economic reforms_ . In other words, we normalize the number of economic reform articles about a country by the total number of articles about that country. For country in year , the index has the following form R R R R I = 100 ×ii E E E tt <u>,</u> ~~.~~ iiEE R RREERREE AARRttiiEEAARRssii tt CChaat IIRRIIii,tt TTEEttTTAA AARRttiiEEAARRssii,tt The reform chatter index can be classified by source: local news (e.g., UAE newspapers writing about the UAE), GCC international news (e.g., Bahraini newspapers writing about the UAE), and non-GCC international news. The index can also be classified into different reform topics based on topic analysis techniques. Appendix A5 provides a detailed description of the topic analysis as well as its findings.

Figure IV.1 shows the overall index and the subindices by source type. The reform chatter index for the GCC is in the same range as emerging G20 countries in recent years. However, Saudi Arabia has the highest chatter index in recent years, much higher than the emerging G20 average. In addition, reform talks spike around important years. For example, the chatter index rises for Bahrain and Oman around the Arab Spring, indicating a response of economic reform discussions to political pressure. Saudi Arabia has seen a strong rise in reform chatter, consistent with its significant reform agenda in recent years. The figures also show how reform chatter from local sources is consistently lower than that from international sources in many GCC countries, except Qatar. This finding suggests a _relative_ disengagement from economic reform discussions from local media and potentially other local stakeholders.

Another aspect of the relative local disengagement is that reform chatter in local media is less responsive to economic shocks than international media. We focus on commodity price shocks (which is dominated by oil price for the GCC countries).<sup>10</sup> When commodity prices are low, chatter in the GCC increases. Interestingly, in these moments, chatter rises more significantly in international news than in local news (see Figure IV.2), pointing to relative disengagement with economic reforms from local media.

> 10 A commodity price shock of a country at time is constructed by Gruss and Kebhaj (2019), as follows = ∑ )Ω , where is the price of commodity in year ; Ω denote commodity-specific average share of commodity tt in the country’s export. For the GCC, oil constitute a big share of exports. JJ tt Δ log(CCR CCII) jj=1 jj,tt jj jj,tt jj Δlog (CC CC jj tt

> jj 12
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<!-- Start of picture text --> 0.025 .—— Oman —— Saudi Arabia<br>— Kuwait — United Arab Emirates<br>0.020 -—— Qatar — Bahrain<br>a<br>S 0.015 f \<br>~~ F ‘<br>©- oo10 LoxaNA "<br>E WH<br>5 Say) iP DY g<br>0.006 RY LF Wh<br>0.000 --- ee i<br>-0.005<br>s sr s ~~ s° a<br><!-- End of picture text --> <!-- Start of picture text --> ——— GCCLocal International<br>0.020) ~~ _Non-GCC International<br>Doo<br>0.015<br>5<br>3<br>i<br>= 0.010<br>°<br>0.005<br>2011 2012,-«-2013, 2014. 20152016. »«= 2017. = 2018» 2019-2020<br><!-- End of picture text --> <!-- Start of picture text --> 0.025 —— ao | ntemational<br>—— Non-GCC International<br>0.020<br>x<br>& 0.015<br>£<br>5<br>E 0.010<br>3<br>0.000<br>2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020<br><!-- End of picture text -->

<!-- Start of picture text --> 0.035 7 —————— GCCNon-GCCLocalInternationalInternational<br>0.030<br>0.025<br>3<br>F 020<br>£<br>= 0.015<br>Ty<br>”<br>0.010<br>0.005<br>0.000 }----~------------------22--n<br>anon nnn nnn annennn anne n anne nn nnn n nnn nnnn nnnnnnnnee<br>2011 2012 2013 2014 2015 2016 2017 2018 2019 2020<br><!-- End of picture text --> <!-- Start of picture text --> 0.08- ——— keGCC Internationali<br>007 —— Non-GCC International<br>0.06<br>3<br>= 005<br>E 0.04<br>=<br>D<br>® 0.03<br>0.02001 Lf NN<br>000<br>"2000 2002-2004 «2006. «= 2008S 010s 12_—«‘iNA:CiNGSSCiéOBHSC«é02O<br><!-- End of picture text -->
Note that sentiment can be interpreted as either support for current economic conditions or current directions of economic reforms, or both. To zoom into sentiment about economic reforms, we examine sentiment on “reform sentences” only. Reform sentences contain the word “reform(s)”. The argument is that these sentences are more likely about economic reforms than about the economic status quo. We manually check a small set of reform sentences in Arabic and English and confirm that these reform sentences do discuss reforms and not the economic conditions. The sentiment divergence remains the same. The sentiment of reform sentences in news articles outside the GCC is consistently more negative than news from the GCC and local news (Panels C and D of Figure IV.4), suggesting that sentiment about economic reforms in the GCC is robustly more negative from the international news.

Two other findings provide indirect evidence to support the argument that reform news articles talk about economic reforms. First, the sentiment of full articles and of reform sentences is highly correlated. Second, sentiment for local and international sources is not significantly correlated with oil price shocks. In other words, reform sentiment does not drop when oil prices drop. This finding suggests reform news articles are more likely to discuss economic reforms than just economic conditions. If news articles discuss the latter, the sentiment (about economic conditions) will likely decline when oil prices drop.

Why does sentiment from outside the GCC matter? We explore whether non-GCC international media sentiment has real effects. One such outcome that attracts great interest is FDI inflows. We find that sentiment about GCC economic reforms in the non-GCC international media is significantly and robustly correlated with the level of FDI inflows to the GCC (see Table A7.1 in Appendix A7).<sup>11</sup> Interestingly, reform chatter is not correlated with FDI inflows. This finding suggests that the support for the current reforms matters for FDI decisions. In other words, “talk is not cheap”. FDI inflows also correlate with the GCC’s GDP growth and trade openness in the same year.

# V. Conclusion

This paper finds that GCC reform efforts have intensified in recent years, as indicated by the rapidly rising number of passed laws and decrees. Nevertheless, the GCC countries tend to pass more laws and decrees in stronger policy areas. Using data from the social media platform Twitter, the paper discovers increasing engagement from the population. In addition, the number of economic reform tweets per engaged user has risen dramatically. Nevertheless, support for economic reforms from the population is declining, suggesting either growing discontent about the current economic situation or shrinking support for the current direction of economic reforms. Data from news media show that international media is more engaged but less positive about the GCC’s economic reforms than local media. These findings suggest a relative disengagement from economic reform discussions by local media (and potentially domestic participants). The more negative tone from international media, which possibly reflects international stakeholders’ views, is noteworthy. Sentiment in international media and social media matters because it is found to be correlated with FDI inflows into the GCC.

> 11  The literature on the determinants of FDI inflows is very broad, covering different regions, time periods, data sets, and employing different methodologies. Some examples include Gammoudi and Cherif (2016) who study the MENA region, Hintosova et al. (2018) for the ‘Visegrad’ countries in Eastern Europe, and Asongu et al. (2018) on the BRICS and MINT countries. Our estimations follow the literature in including variables for GDP growth, inflation, trade openness, and institutional quality, in addition to the media-based variables.

16
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# Appendix

## Appendix A1: A Novel Database of Laws and Decrees in the GCC

Our first contribution is a novel database of past and current economic reforms from all the GCC countries. We obtain these data from each country’s national legislative archives by web-scraping from the following sources:

- **<u>Bahrain:</u>** The Legislation & Legal Opinion Commission (link)

- **<u>Kuwait:</u>** The General Secretariat of the National Assembly (link)

- **<u>Oman:</u>** Oman Law (link)

- **<u>Qatar:</u>** Al-Meezan (Qatar Legal Portal) (link)

- **<u>Saudi Arabia:</u>** National Center for Archives and Record (link)

- **<u>UAE:</u>** The Ministry of Justice (link)

After extracting laws and decrees from the online archives, we tagged them according to a classification system corresponding to the WEF’s Global Competitive Index (GCI) pillars and an additional diversification category corresponding to UNCTAD’s Export Concentration Ratio. We conducted the tagging by creating keywords for each category and searching for those terms in each title. For example, the “innovation” category’s key terms include research, intellectual property, artificial intelligence, technology, inventions, etc. If at least one word in a category’s keywords is found, we apply that category’s tag. We allow for a law to fall under multiple categories. We do not include laws for which we found no category matches in our analysis. The WEF’s GCI pillars and their definitions are in Table A1.1.

### **Table A1.1 Definitions of policy pillars**

|**Pillar**|**Definition**|
|---|---|
||The legal and administrative framework within which<br>individuals, firms, and governments interact to create wealth.|
|_Institutions_|This measure is weighed down by excessive bureaucracy, lack<br>of transparency, corruption, improper management of public<br>finances, etc. Private institutions are also included.|
||Transportation and communications infrastructure, including|
|_Infrastructure_|roads, ports, railroads, air transport, fixed telephone lines, and<br>mobile penetration. The availability and reliability of electricity<br>supplies are also included|
|_Macroeconomic Environment_|Macroeconomic environment’s stability, including fiscal<br>deficits, public debt, inflation rates, and national savings.|
||A general assessment of the population’s health (including|
|_Health and Primary Education_|investment in the provision of health services) and the quality<br>and quantity of basic education|
||Measures secondary and tertiary enrollment rates as well as|
|_Higher Education and Training_|the perceived quality of education by business leaders. Staff,<br>vocational and on-the-job training are also included|
||Measures the ease of trade and doing business, healthy market|
|_Goods Market Efficiency_|competition,<br>absence<br>of<br>restrictions<br>on<br>FDI,<br>buyer<br>sophistication, customer orientation, etc.|
||Measures the flexibility of wages, productivity, female|
|_Labor Market Efficiency_|participation in the labor force, hiring and firing practices, and<br>labor-employer relations. Workplaces must also promote<br>meritocracy|

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|_Financial Market Development_|A combined measure of the amount of capital and capital<br>markets’ efficiency. Measures local equity market size, venture<br>capital availability, ease of accessing loans, regulations of<br>exchanges, banking regulations, and investor rights and<br>protections|
|---|---|
|_Technological Readiness_|The economy’s adoption of existing technologies to enhance<br>productivity, with a focus on ICT. Measures availability of latest<br>technologies,<br>FDI<br>and<br>technology<br>transfer,<br>internet<br>penetration, and firm-level technology adoption|
|_Market Size_|Combined measurement of local and foreign (via exports)<br>market sizes<br>The overall quality of business networks and individual firms’<br>operations and strategies. Measures cluster development,|
|_Business Sophistication_|process sophistication, value chain breadth, competitive<br>advantages, quality and quantity of suppliers, the extent of<br>marketing, etc.|
|_Innovation_|Measures capacity for innovation, R&D spend (both public and<br>private), quality of research institutions, availability of<br>scientists and engineers, and procurement of advanced<br>technology|

Source: World Economic Forum Two of these twelve pillars—market size and business sophistication— cannot be comfortably tagged. Hence, we do not include them.

We include an additional category—Diversification—tied to UNCTAD’s Export Concentration Ratio.

Measures progress in key non-oil sectors into which GCC countries have been attempting to diversify, including tourism, _Diversification_ manufacturing, logistics, SMEs, and financial markets. Any laws containing any element related to these sectors is included Since finding keywords for Business Sophistication and Market Size is difficult, we drop the two pillars. Adding diversification, we establish our eleven legislative categories:

|I.|Institutions|II.|Infrastructure|
|---|---|---|---|
|III.|Macroeconomic Environment|IV.|Health and Primary Education|
|V.|Higher Education and Training|VI.|Goods Market Efficiency|
|VII.|Labor Market Efficiency|VIII.|Financial Market Development|
|IX.|Technological Readiness|X.|Innovation|
|XI.|Diversification|||

Table A1.2 shows the Arabic keywords we used to tag the laws and decrees into pillars.

**Table A1.2 Arabic keywords for policy pillars**

|**Pillar**|**Keywords**|
|---|---|
||منازعات | مظالم | محكمة | محاكم | جزاءات | جزائي | قضاء | قضائي|
||| النیابة<br>| مرافعات |<br>محكوم<br>|<br>عقوب | محامي | محاماة | محاماه | عدال |<br>|
|_Institutions_|قضا | طعن | قانونیة | تحكیم | عدالة | محام | وسائل الثبات<br>|<br>نیابات |<br> <br>|
||<br>محكم | معاقب | احداث<br>| الحداث<br>|لستئنافي<br>| جزائ | جنائي | خدمة|
||<br><br>قاض | مستشار القانون |<br>قضــــائي | كتاب بالعدل | قاضي | فساد | ھدایا|

21
||| رقابة | تزویر<br>|<br>رشوة | محاسب | مراقبة العامة | مناقص|<br>| مزاید<br>مشتریات الحكومیة | حوكمة | شفافیة | مدققي الحسابات<br>| تدقیق | التستر<br>|<br>المزاد | غسیللموال|<br>إعادة تنظیم | إعادة تشكیل | تخویل|<br>جزاء| عدل|
|---|---|
|_Infrastructure_|سكك الحدید<br>| المرور<br>| شاحنات<br>|<br>سیار<br>| حافل |<br>طرق | النقل العام<br>|<br>الجرة<br>| ركاب<br>| بحار<br>|<br>میناء<br>| موانئ<br>| لوجست<br>| تصادم<br>| خطوط الحدید<br>| السیر<br>| حوادث<br>| طائر<br>| طیران<br>|<br>النقل<br>| مركب<br>| موانيء<br>| مخازن<br>|<br>مواصلت<br>| قیادة<br>| ترانزیت<br>| الشحن<br>|<br>شوارع<br>| بضائع<br>| خطوط حدید<br>|<br>قوارب<br>|<br>كھربائي<br>|<br>كھرباء<br>| البنیة التحتیة<br>| بنیة تحتیة<br>|<br>بنیھ تحتیھ<br>|<br>البنیھ<br>التحتیھ<br>| ھاتف<br>| انباء<br>| أنباء<br>| اتصال<br>| إذاع<br>| اعلم<br>|<br>انترنت<br>| إنترنت<br>|<br>إتصلت<br>|<br>تیلیفون<br>| ھواتف<br>| قمار الصناع<br>| قمار صناع<br>| قمر الصناع<br>|<br>قمر صناع | رادیو|<br>سفن|<br>مطار<br>|<br>بحري|<br>برید|<br>جوي|
|_Macroeconomic Environment_|ضریب | ضرائب | قیمة مضاف | التھرب المالي | الفائدة<br>| مؤسسة النقد<br>العربي<br>| سندات<br>|<br>نقود<br>| نقد<br>|<br>كمیة المال<br>|<br>بنك مركزي<br>|<br>عملة<br>| تضخم<br>|<br>ودیع<br>| ودائع<br>| قطر المركزي<br>| البنوك المركزي<br>| المصرف المركزي<br>|<br>البنك المركزي<br>| البحرین<br>المركزي<br>| الكویت المركزي<br>| السیاسة المالیة<br>|<br>میزاني<br>|لقتراض الحكومي<br>|<br>اقتراض حكومي<br>| الدین الحكومي<br>|<br>قرض<br>| قروض |<br>دین حكومي<br>| انفاق<br>| إنفاق<br>|<br>مصروف<br>| سیاسة مالیة<br>| دیون<br>| تقشف<br>| موازنة<br>| دین العام<br>| سندات الحكومیة<br>| سندات حكومیة<br>|<br>عجز|<br>لقتراض<br>| حساب جاري<br>| الحساب الجاري<br>| صكوك<br>| حساب الختام<br>|<br>موازنة<br>| خزینة<br>|<br>دعم المال<br>| قروض سكنیة<br>|<br>القروض السكنیة<br>| تأمین<br>التعاون<br>| صرف بدل<br>| مساعدات<br>| الدعم السكني<br>|<br>إعانة<br>| ضمان<br>لجتماعي<br>| ضمانلجتماعي<br>|<br>تأمینلجتماعي<br>| دعم المادي<br>| الدعم التشغی<br>لي<br>|<br>صندوق الدعم<br>| دعم تمویل<br>| صندوق دعم<br>| دعم مال<br>| دعم السرة<br>| دعم<br>لسر| صندوق لدعم<br>| دعم مستلزمات<br>|<br>دعملقتصاد<br>| برنامج الوطني<br>لدعم<br>| دعم إدارة المشروعات<br>| تأمین اجتماعي<br>| صندوق دعم<br>| حساب<br>المواطن<br>|<br>دعم الجمعیات<br>| دعم الخطوط<br>| دعم التعلیم<br>| دعم<br>مشاریع<br>|<br>صرف الدعم<br>| دعم المنشآت<br>| دعم المزارعین<br>|<br>دعم المشاریع<br>| رواتب<br>|<br>راتب| معاشات<br>| علو<br>| صندوق التقاعد<br>|<br>التأمین ضد<br>| غرامات<br>| حسابات<br>حكوم<br>|<br>صندوق العائلي<br>|<br>وزارة المالیة<br>| الماللحتیاطي<br>| حسابات الختامي<br>| احتیاطي<br>الجیال<br>| تامین التكمیلي<br>|<br>لمو<br>ال العامھ<br>| مال الحتیاطي<br>|<br>مدفوعات الوطنیة<br>| المال العام<br>| شؤون المالیة<br>|<br>موازنة<br>العامة<br>|<br>تأمینات<br>لجتماعي|<br>رسوم|
|_Health and Primary Education_|<br> <br>الصحة | فیروس<br>| صحي<br>| صیدل | أدویة<br>| دواء | تدخین<br>| الوقایة | تبغ |<br>مخدرات<br>| إخصاب<br>| مرض<br>|<br>علج<br>| تطعیم<br>|<br>بیطر<br>| صحھ<br>| امراض<br>|<br>عیادات<br>| مخدر<br>|COVID |<br>كوفید<br>| كمـام<br>| ستیروید<br>|<br>السائل المنوي<br>|<br>المراض<br>| ملریا<br>| عقاقیر<br>| مسكرات<br>| إسعاف<br>| ادویة<br>| مستشفیات<br>|<br>مستشفى<br>| مادة الوراثیة<br>|<br>السرطان<br>| السكري<br>| حضان<br>| تأمین الصحي<br>|<br>تأمینات الصحي | انفلونزا<br>| الیدز<br>|<br>الحمى<br>| سیجارة<br>|<br>طبي |<br>المیة|
|_Higher Education and Training_|<br> <br> <br> <br> <br> <br> <br> <br><sup>تدریب</sup><br>| جامعات | جامعة<br>| كلیة | كلیات | طلبة<br>| مدارس<br>| طلب | جامعي<br>| مدرس | جامعھ | دراسي | معلمین|<br>تعلیم<br>|
|_Goods Market Efficiency_|<br> <br>تنافس<br>| ملكیة فكریة |<br>ملكیة الفكریة |<br>منافس<br>| المناطقلقتصادي<br>| قیاس<br>|<br>أداء<br>| التحول الوطني<br>| احتكار<br>|<br>خصخصة<br>| سعر<br>|<br>أسعار<br>| أسعار<br>|<br>تلعب<br>|<br>تسعیر<br>| مستھلك<br>| مقاییس<br>| معاییر<br>| معایرة<br>| قیاس<br>|<br>منطقة الحرة<br>| مناطق الحرة<br>| مناطق حرة<br>| مناطق التطویر الخاصة<br>|<br>حقوق العملء<br>| مناطق الحره<br>| الشراكة بین<br>القطاعین<br>|<br>منطقةلقتصادیة<br>|<br>تخصیص<br>| علمة الجودة<br>| جمارك<br>|<br>تبادل<br>| تجار |<br>جمرك<br>| واردات<br>|<br>اا<br>اا<br> <br>ا ة<br>ا قط<br>|
||ستیرد<br>| صدرت<br>|<br>إیرد | دمغ<br>| تدول | تسی<br>| تصدیر|
||<br> <br> <br> <br> <br>بطالة | تفنیش | تسریح | وظیفة | وظائف | نقابة | نقابات | التعطل<br>| موظف|
|_Labor Market Efficiency_|<br> <br>| بطالھ<br>|<br>وظیفي<br>|<br>راتب<br>| رواتب<br>|<br>وزیر العمل<br>| تقاعد<br>|<br>موارد البشریة<br>|<br>موارد بشریة | علوة | مھن | تقاعد | استقطاب | معاشات | مكافآت ||

22
||توطین<br>|| بحرنة | تقطیر تعمین| سعودة | تكویت<br>| سوق العمل<br>| الجزاءات<br>المالیة<br>|<br>حمایة الجور<br>| قانون العمل<br>| ساعات العمل<br>|<br>القوى العاملة<br>|<br>مواعید العمل<br>| وزارة العمل<br>| نظام العمل<br>|<br>عقد العمل<br>| اصابة عمل<br>|<br>مزاولة العمل<br>| العمل المؤقت<br>| تصاریح العمل<br>| میثاق عمل<br>| إقامة<br>| اقامة<br>|<br>توظیف|<br>عمال<br> <br> <br>|
|---|---|
|_Financial Market Development_|سیولة | سھم | إكتتاب<br>| سوق المال | أسواق المال | بنك | إف لس<br>| السوق<br>| بنوك<br>| القانون المالي<br>|<br>اكتتاب |<br>استثمار<br>| مستثمر<br>|<br>استثمر| رأس مال<br>|<br>تمویل<br>| أموال<br>|<br>مصارف<br>| صكوك<br>|<br>قطاع المالي<br>| بورصة<br>| سوق السھم<br>| مصرفي<br>| السناد<br>| بنوك<br>| افلس<br>| شیك<br>| إعسار<br>|<br>تسلیف<br>| أوراق المالیة<br>| مستندات الصرف<br>| كفایة<br>المالیة<br>| صرافة<br>| غسیللموال|
||إحصاء | احصائي | معلومات | كمبیوتر | إحصاء | إحصائي | الكتروني |<br> <br>|
|_Technological Readiness_|إلكتروني<br>|<br>تقنیة<br>| حوسبة السحابیة<br>| حاسبات اللي<br>| الحاسب الل<br>|<br>|
|_Innovation_|<br> <br> <br> <br> <br> <br>حواسب اللي<br>ابحاث| اختراع | بحوث | مختبرات<br>| الذكاءلصطناع | دراسات | أبحاث|<br>فضاء | معرفي | تكنولوجیا<br>| ملكیة فكریة |<br>ملكیة الفكریة<br>|
|_Diversification_|سیاح<br>| تأشیر<br>| سفریات<br>| عطلت | المنشآت الصغیرة<br>| المؤسسات الصغیرة<br>| مؤسسات متناھیة الصغر<br>|<br>مشروعات الصغیرة<br>| شركات الصغیرة<br>|<br>مشاریع الصغیرة<br>|<br>ھایدرو كاربون<br>| تعدین<br>| صناع<br>| مصنع<br>| معادن<br>|<br>معدني<br>|<br>مصانع<br>| ألمنیوم<br>| فنادق<br>|<br>متاحف<br>| متحف<br>| معارض<br>| فندق<br>|<br>مھرجان<br>| كیماوي<br>|<br>سكك الحدید<br>| بحار<br>| میناء<br>| موانئ<br>| لوجست<br>|<br>خطوط الحدید<br>| طائر| طیران<br>| موانيء<br>| جوي<br>|<br>مخازن<br>| ترانزیت<br>|<br>الشحن<br>|<br>بضائع<br>| مـوان<br>ئ<br>| خطوط حدید<br>| كیمیائي<br>| سیولة<br>| سھم<br>| إكتتاب<br>| سوق المال<br>|<br>أسواق المال<br>بنك |<br>| إفلس<br>| السوق<br>| بنوك<br>| القانون المالي<br>|<br>اكتتاب |<br>استثمار<br>| مستثمر<br>|<br>استثمر<br>|<br>رأس مال<br>| تمویل<br>| أموال<br>|<br>مصارف<br>| صكوك<br>|<br>قطاع المالي<br>| سوق السھم<br>|<br>مصرفي<br>| السناد<br>|<br>بورصة<br>|<br>افلس شیك<br>| إعسار|<br>تسلیف<br>| أوراق المالیة<br>|<br>مستندات<br>|<br>الصرف| كفایة المالیة<br>| صرافة<br>| غسیللموال<br>سفن |<br>|<br>مطار<br>|<br>بحر<br>|<br>جوي|

Table A1.3 provides loose English translations for the terms in Table A1.2. Please note the translations are mostly in spirit, rather than literal, to retain the content of these laws.

# **Table A1.3 Translations of Arabic keywords for policy pillars**

|**Pillar**|**Keywords**|
|---|---|
|_Institutions_|Dispute, grievance, court, penal, judge, judicial, prosecution, plead,<br>accused, punishment, lawyer, justice, legal, adjudication, means of<br>proof, juvenile, appeal, legal counsel, judicial services, notary,<br>corruption, gifts, monitoring, audit, bribery, forgery, accountant, public<br>monitoring, tender, auction, public/government purchase, governance,<br>transparency, account auditor, cover up, money laundering, restructure|
|_Infrastructure_|Railway, transportation, traffic, truck, car, bus, road, public<br>transportation, taxi, passenger, marine, port, logistics, collision,<br>accident, plane, aviation, vehicle, storage, driving, transit, cargo, street,<br>goods, ship, boat, electricity, electrical, infrastructure, telephony, news<br>agency, broadcast, communications, media, internet, phone, satellite,<br>radio, airport, post|
|_Macroeconomic_<br>_Environment_|Tax, value add, evasion, interest, Arab Monetary Fund, bonds, currency,<br>monetary supply, central bank, inflation, deposit, fiscal policy, budget,<br>budgetary, public/government borrowing, loan, government bonds,|

23
deficit, current account, sukuk, ending balance, balance, treasury, financial support, housing loans, aid, social welfare, social security, support fund, support financing, family subsidy, support needs, support economy, national program to support, project administration subsidy, citizen account, support associations, support lines, educational subsidies, disbursement support, support entities, farmer subsidies, project subsidies, wages, salaries, bonus, retirement fund, insurance against, fines, public/governmental accounts, family fund, Ministry of Finance, reserves, ending balance, generational reserve, supplementary insurance, public finds, national payments, financial affairs, public budget, fees Health, virus, pharma, medicines, drugs, smoking, preventative, tobacco, fertility, disease, cure, treatment, vaccination, veterinary, clinics, anesthetic, COVID, steroid, ambulance, hospital, DNA, cancer, diabetes, nursery, health insurance, influenza, AIDS, fever, cigarette, medical, illiteracy _Health and Primary_ clinics, anesthetic, COVID, steroid, ambulance, hospital, DNA, cancer, _Education_ diabetes, nursery, health insurance, influenza, AIDS, fever, cigarette, medical, illiteracy _Higher Education and_ Training, university, college, student, school, collegiate, teacher, _Training_ educational, education Competition, intellectual property, compete, economic zone, measurement, instrument, national transformation, monopoly, _Goods Market_ privatization, price, pricing, manipulation, consumer, standards, _Efficiency_ measurement, measuring, free zone, special development zone, worker rights, public-private partnership, quality assurance, tariff, trade, customs, import, export, stamp, installment Unemployment, lay off, firing, job, union, employee, of employment, salary, wage, Minister of Labor, retirement, human services, bonus, profession, bonus, attract labor, nationalization, Bahrainization, _Labor Market_ Qatarization, Saudization, Kuwaitization, Omanization, labor market, _Efficiency_ financial rewards, wage protection, rent protection, labor law, working hours, Ministry of Labor, work contract, work system, labor force, parttime work, workplace injury, work permit, charter, laborer, employing, conduct business Liquidity, stock, public offering, subscription, financial market, bank, bankruptcy, the market, financial law, investment, investor, invest, _Financial Market_ capital, financing, monies, sukuk, financial sector, borse, stock market, _Development_ banking, listing, check, insolvency, borrowing, securities, exchange documents, financial adequacy, teller, money laundering, _Technological_ Statistics, statistical, information, computer, electronic, information _Readiness_ technology, cloud computing Research, invention, studies, laboratories, artificial intelligence, space, _Innovation_ knowledge, technology, intellectual property Tourism, visa, travel, vacation, small enterprises, small companies, small projects, hydrocarbon, mining, manufacturing, factory, mineral, aluminum, hotel, museum, exhibition, festival, chemical, railways, marine, port, logistics, aviation, airplane, storage, transit, cargo, goods, _Diversification_ port, financial market, securities, public offering, invest, investor, investment, capital, financing, monies, bank, bankruptcy, financial law, sukuk, financial sector, stock market, exchange documents, financial adequacy, banking, money laundering, ships, airport 24
Table A1.4 provides the total number of laws and decrees. Figure A1.2 shows the number of laws and decrees by policy pillars over time for the 6 GCC countries. They are rising rapidly in recent years, especially the laws and decrees associated with “Diversification”.

**Table A1.4 Cumulative Number of Laws and Decrees (1980-2019)**<sup>**12**</sup>

||**Bahrain**|**Kuwait**|**Oman**|**Qatar**|**Saudi Arabia**|**UAE**|
|---|---|---|---|---|---|---|
|**Diversification**|1652|833|1371|978|701|654|
|**Financial Market Development**|655|415|387|390|298|246|
|**Goods Market Efficiency**|1109|322|898|703|347|721|
|**Health and Primary Education**|588|70|415|210|258|207|
|**Higher Education and Training**|765|217|543|188|231|227|
|**Infrastructure**|958|363|821|666|411|517|
|**Innovation**|95|87|45|86|72|64|
|**Institutions**|1761|287|614|1376|377|435|
|**Labor Market Efficiency**|979|75|714|420|523|264|
|**Macroeconomic Environment**|900|2052|949|559|400|501|
|**Technological Readiness**|220|87|52|77|139|102|
|**Others (not matched)**|6602|3045|4289|3870|2394|2579|
|**Country Total across all Categories**|12361|4345|7322|7052|3837|3762|

Though notable differences exist, the GCC countries have four primary sources of laws and decrees: 1) Royal Resolutions and Decrees, 2) the Council of Ministers/Cabinet, 3) individual ministerial decrees and resolutions, and 4) other, including parliament, administration and authorities. Figure A1.1 breaks down the source of laws from 1980 to 2019. Kuwait stands out as a country that has many laws from the National Assembly. In other countries, royal and ministerial sources play an important role.

**Figure A1.1: Sources of laws and decrees by country (1980-2019)**

<!-- Start of picture text --> 100%<br>80%<br>60%<br>40%<br>20%<br>0%<br>Bahrain Kuwait Oman Qatar Saudi Arabia UAE Federal<br>Cabinet Constitutional Ministerial<br>National Assembly Others Royal<br>Supreme Council Presidential UAE Federal Supreme Council<br><!-- End of picture text --> 12 The last row accounts for double counting, so the figures will differ from the sum of all preceding rows.

25
BE Dwversification B Health and Primary Education Bf Innovation B Macroeconomic Stability B§ Finandal Market Development B§ Higher Education 8 Institutions B Technological Readiness § Goods Market Effidency B infrastructure @ Labor Market Efficiency
# Appendix A2: Do Reform Efforts Focus on Lagging Policy Areas?

The World Economic Forum’s Global Competitive Index (GCI) measures each country’s performance across the policy pillars through unit-less ‘progress scores’ on a scale of 0 to 100 (100 being the highest performance). Formally, each indicator is scaled according to the formula below: p = <u>, ,</u> R R <u>, ,</u> ∗100 R R R ii EE tt ii EE tt vvaav RR −wwR pptt ppR aaIIssRR ii,EE,tt We scale these progress scores into distance-to-frontier metrics as: ppR ppR ppssR RR RRIIttiiR ii,EE,tt −wwR pptt ppR aaIIssRRii,EE,tt p The GCI has all twelve indices for each of the six GCC countries from 2007 to 2017. This period is the only IIiippttaaIIssRR ttRR R RRIIttiiR ii,EE,tt = 100 − ppR ppR ppssR RRii,EE,tt The GCI has all twelve indices for each of the six GCC countries from 2007 to 2017. This period is the only time where the GCI scores are methodically consistent and comparable across years.

The final source, UNCTAD’s Export Concentration Ratio (also known as the Herfindahl-Hirschmann Index), measures a country’s export market concentration as follows: where Hc is the index for country _c_ , xi is the value of exports for product _i_ , X is the sum of export values across all products, and n is the number of products. We rescale the index so that 0 is the least concentrated portfolio while 100 is the most concentrated. This transformation allows us to include diversification as an additional ‘pillar’ to complement the GCI’s ten. We obtain for each GCC country for the years 2007 to 2017. Table A2.1 shows the average Distance to Frontier. Overall, the GCC performs well in Macroeconomic Environment, Health and Primary Education, and is underperforming in Diversification, Innovation and Technological Readiness.

**Table A2.1 Average Distance to Frontier (2007-2017)**

||**Bahrain**|**Kuwait**|**Oman**|**Qatar**|**Saudi**<br>**Arabia**|**UAE**|**GCC**<br>**Average**|
|---|---|---|---|---|---|---|---|
|**Diversification**|32.6|68.4|55.8|52.9|70.1|32.9|52.1|
|**Financial Market Development**|29.8|49.0|39.3|25.8|39.4|33.0|36.0|
|**Goods Market Efficiency**|24.7|51.3|35.0|18.8|31.2|13.4|29.1|
|**Health and Primary Education**|17.8|29.9|28.9|11.9|24.6|18.3|21.9|
|**Higher Education and Training**|36.4|52.8|48.1|30.1|37.9|30.4|39.3|
|**Infrastructure**|33.8|48.1|36.8|30.8|34.9|12.2|32.8|
|**Innovation**|67.9|75.4|64.4|36.3|53.0|45.5|57.1|
|**Institutions**|30.9|48.8|25.8|12.5|28.4|15.9|27.1|
|**Labor Market Efficiency**|40.2|55.2|48.2|30.0|50.6|27.8|42.0|
|**Macroeconomic Environment**|32.9|6.2|17.2|10.3|16.4|17.1|16.7|
|**Technological Readiness**|34.7|57.5|55.1|32.4|44.6|25.4|41.6|
|**Country Average across**<br>**Categories**|34.7|49.3|41.3|26.5|39.2|24.7|36.0|

Note: 100 is farthest away from the frontier 27
To investigate whether GCC countries focus on areas farthest from the frontier, we utilize the following specification in a Poisson regression (given that the outcome variable is a count): ii,EE,tt ii,EE,tt−1 EE,tt ii,EE,tt where LLaawwpp CCaap RRII is the count of laws and decrees passed for pillar = αα + DDiippttaaIIssRR ttRR FFR IIttiiR + TTRRttaavv LLaawwpp CCaap _i_ in country RRII + εε _c_ in year _t;_ measures the performance for pillar _i_ in country _c_ in year _t-1_ (i.e. lagged) on ii,EE,tt a scale of 0-100 (with 100 being the worst) and LLaawwpp CCaap RRII is the total number of laws and ii,EE,tt−1 decrees country DDiippttaaIIssRR ttRR FFR _c_ IIttiiR passed in year _t_ . We present the results in Table A2.2. We run five specifications: EE,tt TTRRttaavv LLaawwpp CCaap RRII

1. With country and year fixed effects

2. With country and pillar fixed effects 3. With country, year and pillar fixed effects 4. With country and year fixed effects, along with interactions of country and lagged distance to policy frontier 5. With country, year and pillar fixed effects, along with interactions of country and lagged distance to policy frontier Regardless of specification, the coefficient for the lagged distance to frontier is statistically significant and negative (see Table A2.2), indicating that the GCC countries pass reforms in areas of strength rather than weakness. Saudi Arabia focuses more on weaknesses than other GCC countries (see column [4]- the coefficient is the most positive, indicating the most positive relationship between Distance to Frontier and Law Count). The country fixed effects allow us to interpret the finding as follows: within a country, the number of laws and decrees passed rises relatively more in improving policy pillars. The pillar fixed effects take care of a potential concern that a policy pillar could be over- or under-tagged due to keyword choice.

The findings are subject to caveats. First, the timeframe spans 2008 to 2018, so the GCC countries may have corrected focus in recent years. Second, reforms need not be pushed through as legislative reforms, as improvements in operations and procedures could close the gap to the frontier. Another explanation for the finding is that countries enter a ‘virtuous cycle’ whereby they have more capacity to implement reforms in areas of pre-existing strength. There might also be an argument about the sequencing of reforms. The “right” reforms are not necessarily on weak policy areas but the most logical next step (see Edwards, 2009; <mark>Feltenstein and Nsouli, 2003</mark> ).

28
**Table A2.2 Number of Laws and Decrees vs. Distance to Frontier (Lagged)**

|Poisson Regression|Depende<br>|nt Variable:<br>|Laws and D<br>|ecrees Pass<br>|ed,Count<br>|
|---|---|---|---|---|---|
||(1)|(2)|(3)|(4)|(5)|
|**Distance to Frontier, Lagged**|**-0.013**<sup>*******</sup>|**-0.010**<sup>*******</sup>|**-0.010**<sup>*******</sup>|**-0.018**<sup>*******</sup>|**-0.008**<sup>*******</sup>|
||(0.001)|(0.001)|(0.001)|(0.001)|(0.002)|
|Total Laws Passed in Country-Year|0.002<sup>***</sup>|0.002<sup>***</sup>|0.002<sup>***</sup>|0.002<sup>***</sup>|0.002<sup>***</sup>|
||(0.0002)|(0.0001)|(0.0002)|(0.0002)|(0.0002)|
|Kuwait|-0.153<sup>**</sup>|0.014|-0.190<sup>**</sup>|0.216<sup>**</sup>|0.502<sup>***</sup>|
||(0.073)|(0.057)|(0.074)|(0.094)|(0.102)|
|Oman|-0.093|0.058|-0.126<sup>*</sup>|-0.423<sup>***</sup>|-0.479<sup>***</sup>|
||(0.067)|(0.052)|(0.068)|(0.096)|(0.104)|
|Qatar|-0.132<sup>***</sup>|0.035|-0.085<sup>*</sup>|-0.422<sup>***</sup>|-0.026|
||(0.046)|(0.037)|(0.046)|(0.068)|(0.074)|
|Saudi Arabia|-0.069|0.123<sup>**</sup>|-0.063|-0.930<sup>***</sup>|-0.390<sup>***</sup>|
||(0.066)|(0.051)|(0.066)|(0.092)|(0.095)|
|UAE|-0.378<sup>***</sup>|-0.150<sup>***</sup>|-0.360<sup>***</sup>|-0.034|-0.008|
||(0.073)|(0.057)|(0.073)|(0.095)|(0.101)|
|Year: 2009|0.088<sup>**</sup>||0.094<sup>**</sup>|0.100<sup>**</sup>|0.109<sup>***</sup>|
||(0.041)||(0.041)|(0.041)|(0.042)|
|Year: 2010|-0.085<sup>**</sup>||-0.073<sup>*</sup>|-0.075<sup>*</sup>|-0.047|
||(0.043)||(0.043)|(0.043)|(0.043)|
|Year: 2011|-0.057||-0.032|-0.039|-0.003|
||(0.042)||(0.043)|(0.043)|(0.043)|
|Year: 2012|-0.035||-0.002|0.007|0.042|
||(0.042)||(0.042)|(0.042)|(0.042)|
|Year: 2013|-0.020||0.015|0.017|0.054|
||(0.042)||(0.043)|(0.043)|(0.043)|
|Year: 2014|0.067||0.101<sup>**</sup>|0.094<sup>**</sup>|0.132<sup>***</sup>|
||(0.042)||(0.043)|(0.043)|(0.043)|
|Year: 2015|0.023||0.066|0.032|0.078<sup>*</sup>|
||(0.043)||(0.043)|(0.044)|(0.044)|
|Year: 2016|-0.030||0.003|-0.024|0.008|
||(0.045)||(0.046)|(0.046)|(0.046)|
|Year: 2017|0.162<sup>***</sup>||0.193<sup>***</sup>|0.160<sup>***</sup>|0.191<sup>***</sup>|
||(0.044)||(0.044)|(0.044)|(0.044)|
|Year: 2018|0.139<sup>***</sup>||0.171<sup>***</sup>|0.132<sup>***</sup>|0.177<sup>***</sup>|
||(0.045)||(0.045)|(0.045)|(0.045)|
|Financial Markets||-1.054<sup>***</sup>|-1.055<sup>***</sup>||-1.002<sup>***</sup>|
|||(0.037)|(0.037)||(0.037)|
|Goods Markets||-0.596<sup>***</sup>|-0.597<sup>***</sup>||-0.549<sup>***</sup>|
|||(0.034)|(0.034)||(0.035)|
|Health and Primary Education||<br>-1.598<sup>***</sup>|<br>-1.601<sup>***</sup>||<br>-1.553<sup>***</sup>|
|||(0.046)|(0.046)||(0.047)|
|Higher Education and Training||-1.241<sup>***</sup>|-1.242<sup>***</sup>||-1.201<sup>***</sup>|
|||(0.039)|(0.039)||(0.040)|

29
|Infrastructure||-0.717<sup>***</sup>|-0.719<sup>***</sup>||-0.687<sup>***</sup>|
|---|---|---|---|---|---|
|||(0.033)|(0.033)||(0.034)|
|Innovation||-2.647<sup>***</sup>|-2.646<sup>***</sup>||-2.636<sup>***</sup>|
|||(0.077)|(0.077)||(0.078)|
|Institutions||-0.306<sup>***</sup>|-0.309<sup>***</sup>||-0.241<sup>***</sup>|
|||(0.032)|(0.032)||(0.033)|
|Labor Markets||-0.860<sup>***</sup>|-0.859<sup>***</sup>||-0.841<sup>***</sup>|
|||(0.034)|(0.034)||(0.035)|
|Macroeconomic Stability||-0.662<sup>***</sup>|-0.663<sup>***</sup>||-0.666<sup>***</sup>|
|||(0.037)|(0.038)||(0.039)|
|Technological Readiness||-2.003<sup>***</sup>|-2.005<sup>***</sup>||-1.984<sup>***</sup>|
|||(0.053)|(0.053)||(0.053)|
|Lag Distance to Frontier * Kuwait||||-0.006<sup>***</sup>|-0.015<sup>***</sup>|
|||||(0.002)|(0.002)|
|Lag Distance to Frontier * Oman||||0.011<sup>***</sup>|0.010<sup>***</sup>|
|||||(0.002)|(0.002)|
|Lag Distance to Frontier * Qatar||||0.012<sup>***</sup>|-0.001|
|||||(0.002)|(0.002)|
|Lag Distance to Frontier * Saudi Arabia||||0.025<sup>***</sup>|0.009<sup>***</sup>|
|||||(0.002)|(0.002)|
|Lag Distance to Frontier * UAE||||-0.016<sup>***</sup>|-0.014<sup>***</sup>|
|||||(0.002)|(0.003)|
|Constant|3.042<sup>***</sup>|3.517<sup>***</sup>|3.754<sup>***</sup>|3.109<sup>***</sup>|3.594<sup>***</sup>|
||(0.089)|(0.079)|(0.095)|(0.096)|(0.104)|
|Observations|726|726|726|726|726|
|Log Likelihood|-5,834.873|-3,319.760|-3,277.996|-5,598.916|-3,119.799|
|Akaike Inf. Crit.|11,705.750|6,675.521|6,611.992|11,243.830|6,305.599|

Notes: Clustered standard errors in parentheses. *p**p***p<0.01. The sample covers 2008 to 2019 for the 6 GCC countries and 11 policy pillars.

We use media to identify reforms perceived as important by the media. To identify articles introducing new reforms, we use the corpus of articles in English and focus on article titles.<sup>13</sup> In total, there are around 63,000 articles in English in our data set. Then, we use keyword searches to locate article titles that include at least one of the following 13 terms: ‘reform’; ‘unveil’; ‘adopt’; ‘introduce’; ‘implement’; ‘roll out’/’rolls out’; ‘reveal’; ‘announce’; ‘sign’; ‘approve’’; ‘declare’; ‘present; ‘outline’. From this subset, we manually select the titles which correspond to reform announcements. This selection process yields 595 reform announcements over the sample period. Finally, we categorize each article into one (or more) of the 11 GCI pillars. These data – at the country-year-pillar level – form the basis of our analysis. Finally, we generate a reform announcement index, the number of articles announcing reform in a country-year normalized by the number of English reform articles in that country-year. Figure A2.1 summarizes the aggregate evolution of reform announcements in the GCC.

> 13 Although we only consider articles in English in this exercise, since our objective is to identify ‘major’ reforms in the media, it is likely these will be covered in both English and Arabic.

30
Figure A2.1: Aggregate reform annoucement in the GCC <!-- Start of picture text --> 2.2<br>2<br>1.8<br>1.6<br>1.4<br>1.2<br>1<br>.8<br>.6<br>.4<br>.2<br>2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020<br>Year<br>Reform Announcements Index<br><!-- End of picture text --> Note: Reform announcement index captures the number of articles announcing reform in GCC in a year normalized by the number of English reform articles in a year Using the media to filter what is perceived as important reforms, a similar finding emerges: the GCC countries did not pass more reforms, perceived as important and covered by the media, in areas of weakness. Table A2.3 shows that a pillar’s lagged distance to frontier is not significantly correlated with reform announcements about that pillar.

**Table A2.3: Lagged Distance to Frontier and Reform Announcements**

|Dependent Variable:|(1)<br>Reform Announcements<br>Count|(2)<br>Reform Announcements<br>Index|
|---|---|---|
|Estimation:|Poisson|OLS|
|Distance to Frontier t|-0.0172|-0.00131|
||(0.0147)|(0.00165)|
|Distance to Frontier t-1|0.00676|0.000152|
||(0.0134)<br>|(0.00180)<br>|
|Country FE|<br>|<br>|
|Year FE|||
|Reform Pillar FE|||
|R2||0.122|
|pseudo R2|0.399||
|Number of Countries|6|6|
|Observations|660|660|

_Notes:_ This table presents the effect of the distance to the frontier along 11 reform pillars on reform announcements captured in the media. The dependent variable in Column 1 is the number of articles announcing reform in a country-year-reform pillar. The dependent variable in Column 2 is the number of articles announcing reform in a country-year-reform pillar normalized by the number of English reform articles in that country-year. Column 1 is estimated using Poisson; Column 2 is estimated using OLS. The distance to frontier measure is on a scale of 0 to 100, where 100 denotes the _farthest_ distance from the frontier along a given reform pillar. Standard errors are clustered at the country level and papered in parentheses, where<sup>*</sup> _p_ < 0.10,<sup>**</sup> _p_ < 0.05,<sup>***</sup> _p_ < 0.01 31
# Appendix A3: Twitter Data Analyses

We collect tweets in Arabic from 2009 to mid-2020. However, our dataset starts from 2011 due to data availability issues for the 2009-2010 period. To filter data related to reforms from Twitter, we use four keywords in Arabic, as presented below. These four keywords refer to the word ‘reform’ in Arabic in its singular and plural forms as well as with and without an article.<sup>14</sup>

|**اصلحات**|**لصلحات**|**لصلح**|**اصلح**|
|---|---|---|---|

Using these four keywords as a filter, we collect more than **16 million tweets in Arabic** over the 20112020 period.

**Overcoming lexical issues: Multiple meanings to the word ‘reform’ in Arabic:** The first hurdle was not directly related to the data but rather to the multiple meanings of the word ‘reform’ in Arabic. We found out that information collected from Twitter using the term ‘ _reform’_ in Arabic is not necessarily related to social and economic reforms, as the term ‘ _reform’_ in Arabic has many different meanings such as ‘repair’, ‘rehabilitation’, ‘correction’, or ‘reconciliation’. Consequently, the Arabic term for ‘ _reform’_ can also talk about religious topics related to reconciliation. The word ‘ _reform’_ is also the name of many political parties in the region. For instance, we found information referring to the Yemeni war using this filter since ‘reform’ is the name used to call the Yemeni political party ‘Yemeni Congregation for Reform’, ‘ ’التجمع ال�مي ي لإلصالحin Arabic. Consequently, these tweets are excluded. To select the meaning of ‘ _reform’_ we are interested in, we relied on specific topical keywords (see Appendix A5) to keep the relevant tweets and delete the others. After applying this filter, we are left with about 2 million tweets in Arabic about economic reforms.

**Breaking down the data set by country:** To break down the collection of tweets into six data sets (one per country), we link a tweet to a country by detecting keywords such as the country's name (both in Arabic and English) and the name of its capital city. If a tweet contains two GCC countries, it is included in both countries’ data sets. As there are many tweets in which we could not detect the country of origin using these keywords, we leverage the user’s location. Our assumption is when a user declares a country when the user first registers, the user will probably tweet about this country. Nevertheless, to avoid the situation in which a user located in “Country A” is talking about another “Country B” – be it in the GCC or not - we dropped all tweets made by a user containing the name of a country other than its declared location. For example, suppose a user is located in Saudi Arabia in our user’s database. In that case, the tweet will be used if it mentions no other countries and will be deleted if “Egypt” or “United States” appears in the post since the user may be talking about reforms in these countries rather than in Saudi Arabia. To detect the presence of other countries in tweets, we used Name Entity Recognition (NER), a technique that identifies specific entities in the text of each tweet (e.g., person, organization, location, etc.). By adding this technique, we increased our database of tweets from around 420,000 to 635,000 (see Figure III.1).

**Cleaning vocalization marks:** In the Arabic alphabet, each letter can have a vocalization mark. A vocalization mark is an optional symbol giving a hint to the reader on the pronunciation of a letter. However, in our analyses, the same word was considered as two different words depending on if it has

> 14 Note that using these four keywords, we include tweets containing these words written with vocalization marks or any other characters above or below a letter.

32
> nlp_cleaning_ar('3) 2 JS is Gb wh Se Y")
We identify locations as follows: a tweet is considered local if the user’s location is in the same country as the tweet is referring to. For each country, we establish a list of names characterizing a ‘local location’: the names of the country's main cities and multiple ways to write the country's name.

**Sentiment analyses:** In this analysis, we extract people’s perceptions and opinions from tweets about economic and social reforms in the GCC based on the dictionaries of positive versus negative words we manually labeled.

We created three dictionaries by extracting the words most frequently used in the Tweets and then labeling them as positive, negative, or neutral. We considered using existing dictionaries, but we manually created our dictionaries tailored to this specific case. Our dictionaries match the tweets we collected better since they enable us to avoid words with a general meaning different from those in our specific context. The dictionaries we created contain 271 positive words, 307 negatives, and 5113 neutral words. Only positive and negative words are used to compute sentiment.

We count the number of words matching the dictionary of positive words and negative words for each tweet. We then compute the support metric as follows: R<sup>ppRRppiittiivvRR wwRIIpp−# RIIRRppaattiivvRR wwRIIpp</sup> ppvvp tt=<sup># R</sup> The positive or negative sign of the support (as computed above) indicates the tweet's sentiment. ttRRttaavv # R wwR IIpp iiII tthRR ttwwR tt

**An illustration of calculating sentiment:** Below is an example of tweets collected and the steps for text processing and calculating sentiment.

- Source Tweet (in Arabic):

ضر

- Translation of the Tweet in English (only for the example): The tax of reforming what has been corrupted by time is high, and its impact in the short term is limited. So everyone will pay what society has earned in solving the unemployment problem.

- Lemmatized and cleaned Tweet:

- List of positive words matching with our dictionary (1 word): [ ]حل

- List of negative words (4 words): [افسده, عالة, مشكل, بطالة ]

**Qatar** : Ministry of Administrative Development Labor & Social Affairs, General Electricity & Water Corporation, Project Office for the State of Qatar, Public Works Authority, Khaled Ben Khalifa AlThani, Mohamad Ben AbdelRahman, Mohamad AlHamadi.

**UAE** : Office of Foreign Minister International Cooperation, Ministry of Foreign Affairs and International Cooperation, Ministry of Education, Ministry of Justice, Anwar Gargash, Mohamad Ben Rashed AlMakthoum, Hussein AlHammadi, Darar Belhol AlFlasi, Suhail AlMazroui, Thani AlZeyoudi.

**Bahrain** : Ministry of Interior, Ministry of Finance and National Economy, Ministry of Labour & Social Development, Ministry of Education, Ministry of Education, Ministry of Foreign Affairs, Khaled Ben Ahmad. **Oman** : Khalfan AlShueili, Ministry of Education, Royal Oman Police, Badr AlBusaidi, Ministry of Interior, Ministry of Labor, Ministry of Energy and Minerals, Ministry of Health.

34
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# Appendix A4: Economic Reform News

To compile our database of economic reform articles, we use carefully selected keywords in the 28 languages available in the Dow Jones database. In particular, we search for all articles which contain the words ‘economy’ or ‘economic’ _and_ ‘reform’ or ‘reforms’ in the text of the article. Table A4.1 presents our translations of these terms in the 28 languages.

**Table A4.1 Keywords for economic reforms articles**

|Language|Economy|Economic|Reform|Reforms|
|---|---|---|---|---|
|Arabic|اقتصاد||الصلحات<br>||
||اقتصادیة||اصلحات<br>||
||اقتصادي||إصلحات<br>||
||||لصلحات<br>||
||||الصلح<br>||
||||إصلح<br>||
||||لصلح<br>||
||||اصلح||
|Malay|ekonomi|ekonomi|pembaharuan|pembaharuan|
|Indonesian|ekonomi|ekonomis|pembaruan|reformasi|
|Bulgarian|икономика|икономически|реформа|реформи|
|Catalan|economia|econòmic|reforma|reformes|
|Chinese - Simplified|经济|经济|改革|改革|
|Chinese - Traditional|經濟|經濟|改革|改革|
|Czech|hospodářství|hospodářský|reforma|reformy|
|Danish|økonomi|økonomisk|reform|reformer|
|Dutch|economie|economisch|hervorming|hervormingen|
|||economische|||
|English|economy|economic|reform|reforms|
|Finnish|talous|taloudellinen|uudistaa|uudistuksia|
|French|économie|économique|réforme|réformes|
|||économiques|||
|German|wirtschaft|wirtschaftlich|reform|reformen|
|||wirtschaftsreformen|reform|reformen|
|Hungarian|gazdaság|gazdasági|reform|reformok|
|Italian|economia|economico|riforma|riforme|
|||economica|||
|||economici|||
|||economiche|||
|Japanese|経済|経済的|改革|改革|
|Korean|경제|간결한|개정|개혁|
|Norwegian|økonomi|økonomisk|reform|reformer|
|Polish|ekonomia|ekonomiczny|reforma|reformy|

36
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# mondag‘Connecting hhawiedge & pooper Saudi Arabia's New Public Procurement Law

Heinrich Kéllisch 1227 words 19 December 2019 Mondaq Business Briefing BBPUB English (c) 2019 Mondag Lid The Kingdom of Saudi-Arabia (KSA) is the largest economy in the Middle East & North Africa (MENA) region. The country's public spending in infrastructure, health care, transport, and other government-driven sectors is among the highest the MENA region. In an unparalleled program of reform under its Vision 2030, the Kingdom tries to make its economic, social and legal landscape ready for coming generations. As part of this reform, KSA recently enacted a new Public Procurement Law that governs public tenders. This legal briefing gives an overview of the new Public Procurement Law and its key features.

### 1. What is the Public Procurement Law (PPL) and who is concerned by it?

The New Public Procurement Law ("PPL" or “Law’) is the main legal regulation for all government procurement in the KSA. All goverment entities such as the State and its Ministries, Regional Authorities and Municipalities as well as Public Entities with an individual legal personality are subject to this new law.1 The Law regulates how these entities can cater to their needs in terms of procuring goods and services. It should be noted, however, that for certain sectors (especially in relation defence and security), many of the regulations are eased and facilitate an easier approach for the concerned government entities.

The Law establishes several new institutions for the Kingdom's procurement structures. The overarching responsible authority for the Law and its implication will be the Ministry of Finance (MoF). Anew procurement portal, named Etimad (www.etimad.sa +) under the supervision and constant development of the MoF.2 The Law also establishes a Unified Purchase Entity (UPE). The UPE’s assumes several tasks. It is the unit directly interacting with the tendering parties in cases of more than one government entity being involved. It mainly provides background support such as research and quidance to government entities in procurement processes.

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# Appendix A5: Topics of Reform Discussions- Supervised Topic Analyses with News Media

Two big-data approaches are used to analyze reform topics in the paper. The first one is unsupervised topic analyses (i.e., we let the machine learning process identify the topics based on words that frequently go with each other). The second approach uses many topics based on keyword searches, which we will detail here.<sup>16</sup> Utilizing a similar methodology Baker et al. (2016), we tag articles according to 15 categories using lists of key terms. If an article contains at least one sentence with the word 'reform(s)' containing at least one key term in the category, the article receives that category's tag. The 15 categories are as follows: 1) taxation, 2) trade, 3) fiscal policy, 4) monetary policy, 5) financial markets, 6) diversification, 7) nationalization, 8) liberalization, 9) oil/energy, 10) labor, 11) social, 12) political, 13) international, 14) IMF/WB (IMF or World Bank is mentioned) and 15) Vision 2030. These categories were inspired by the results we obtain from the word2vec and LDA analyses, particularly the liberalization, diversification, and IMF/WB tags. The list of keywords for each language is provided below:

## **Arabic keywords**

|**Category**|**Keywords**|
|---|---|
|_Tax_|ضریبة، ضرائب، ضریبي|
|_Trade_<br>|جمارك، جمركة، تبادل، تجار ، جمركیة، واردات، استیراد،<br>صادرات<br>|
|_Monetary_|<sup>السیاسة النقدیة، الفائدة، البنك المركزي، الوراق النقدیة، سندات الحكومة، سیاس ة</sup><br>نقدیة، أوراق نقدیة، كمیة المال،<br>بنك مركزي<br>|
||السیاسة المالیة ، میزانیة،لقتراض الحكومي، اقتراض حكومي ، الدین الحكومي ،|
|_Fiscal_|دین حكومي<br>،<br>انفاق<br>،<br>إنفاق<br>،<br>مصروف<br>،<br>سیاسة مالیة<br>،<br>دیون<br>،<br>تقشف<br>،<br>موازنة<br>،<br>دین<br>العام، عجز،لقتراض، حساب جاري،<br>الحساب الجاري|
||توطین، استبدال العمالة، إستبدال العمالة، القطاع الحكومي، قطاع حكومي،<br>|
|_Nationalization_|<br>بحرنة<br>،<br>تستبدل العمالة<br>،<br>تسریح الوافدین<br>،<br>العمالة الوافدة<br>،<br>العمالةلجنبیة<br>،<br>العمالة<br>،الجنبیة تعمین، سعودة|
|_Liberalization_|<br><sup>انفتاح،</sup><br>إنفتاح،<br>دیمقراطي،<br>دیموقراطي،<br>حریة ،<br>لیبرالي،<br>خصخصة،<br>السوق<br>الحر، قطاع الخاص، إصلح السوق، رفع القیود،<br>شفیافیة السوق|
|_Diversification_|تنویع، تنوع، استدام، مستدام<br>سیولة ، سھم ، تداول ، إكتتاب ، سوق المال، أسواق المال ، الوراق المالیة،<br>،اكتتاب|
|_Financial_|<br>استثمار<br>،<br>مستثمر<br>،<br>استثمر<br>،<br>رأس مال<br>،<br>تمویل<br>،<br>رؤوس أموال<br>،<br>مالیة<br>،<br>مصارف<br>،<br>قطاع المالي، بورصة ،<br>سوق السھم،<br>قطاع المصرفي|
|_Labor_|<br> <br> <br><sup>بطالة، تفنیش، فصل العامل، عمال، تسریح، سوق العمل، وظیفة، وظائف، نقابة،</sup><br>،نقابات راتب، رواتب، عامل، فرص العمل ،<br>قانون العمل|
|_Energy/oil_|<sup>بترول، غاز، نفط، أرامكو، كھرباء، كھربائي، ماء، میاه، مائي، برمیل، أوبك ،</sup><br>طاقة|
|_World Bank/IMF_<br>_Political_<br>|صندوق النقد الدولي ، البنك الدولي ،<br>imf<br>سیاسي، أمن، حرب ، تشریعي، سیاسیة، دستور، امن، طائفي، إرھاب ، ارھاب ،<br>عسكري<br>،<br>دفاع<br>،<br>فساد<br>،<br>أحزاب<br>،<br>شعب<br>،<br>مفسد<br>قمع ،<br>،<br>تطرف<br>،<br>تعصب<br>،<br>حزب<br>،<br>انتخاب، احتجاج ، معارضة، محاسبة، ربیع العربي،<br>احتلل<br>|
|_International_|<br> <br><sup>الولیات المتحدة، روسیا، صین، دولي، عالم، الھند، ایران، مصر ، إیران، الیمن ،</sup><br>سوریا،<br>العراق،<br>الوطن العربي ،<br>التعاون الخلیج،<br>أمریك،<br>فلسطین،<br>الشرق|

16 The first approach does not generate clean outputs but help guide the topic selection in the second approach. The results of the first approach are available upon request.

40
فرنس ، بریطان، األوسط، أوروب، لبنان، أفریق، برازیل، سودان، إقلیم، األسد، سوري األمم، مجلس التعاون، یورو ، أفغانستان، سیاسي، أمن، حرب ، تشریعي، سیاسیة، دستور، امن، طائفي، إرھاب ، ارھاب ، _Social_ ، تعصب ، تطرف ،قمع ،مفسد ،شعب ، أحزاب ،فساد ،دفاع ،عسكري احتالل حزب ، انتخاب، احتجاج، معارضة ، محاسبة ، ربیع العربي، _Vision_ الرؤیة السعودي ، رؤیة۲۰۳۰ ، رؤیة2030

# **English keywords**

|**Category**|**Keywords**|
|---|---|
|_Tax_|'taxed'<br>'taxation',<br>'tax',<br>'taxes',|
|_Trade_<br>_Monetary_|subsidies',<br>'government<br>barrier',<br>'import<br>duty',<br>'import<br>tariff',<br>'import<br>'trade<br>treaty',<br>'trade<br>organization',<br>trade<br>'world<br>'wto',<br>subsidy',<br>'government<br>'gatt',<br>round',<br>'uruguay<br>round',<br>'doha<br>act',<br>'trade<br>policy',<br>'trade<br>agreement',<br>organisation','trading'<br>trade<br>'dumping','trade','import','export','tariff','world<br>operations',<br>market<br>'open<br>supply',<br>'money<br>fed',<br>'the<br>reserve',<br>'federal<br>lending<br>'overnight<br>fundsrate',<br>'fed<br>policy',<br>'monetary<br>easing',<br>'quantitative<br>'discount<br>resort',<br>last<br>of<br>'lender<br>rates',<br>'interest<br>bank',<br>rate','central<br>united<br>the<br>of<br>bank<br>uthority','sama','central<br>a<br>window','saudiarabianmonetary<br>of<br>bank<br>oman','central<br>of<br>bank<br>kuwait','central<br>of<br>bank<br>'central<br>arabemirates',<br>bank','monetary'<br>central<br>bahrain','qatar|
|_Fiscal_|'defense<br>budget',<br>'balanced<br>battle',<br>'budget<br>'budget',<br>spending',<br>'government<br>stimulus','budget<br>'fiscal<br>spending',<br>'entitlement<br>spending',<br>'military<br>ding',<br>spen<br>'fiscal<br>deficit’,<br>'debt','fiscal<br>ceiling',<br>'debt<br>debt',<br>'national<br>debt',<br>'federal<br>deficit',<br>account',<br>budget','fiscal','current<br>the<br>'balance<br>deficit',<br>'government<br>footing',<br>'austere'<br>'austerity',<br>balance',<br>program",'primary<br>account<br>zen's<br>"citi|
|_Nationalization_|'emiratization',<br>sector',<br>support','public<br>'nationalis','nationaliz','state<br>'qatarisation',<br>'qatarization',<br>'omanisation',<br>'omanization',<br>'emiratisation',<br>'bahrainization',<br>'kuwaitisation',<br>'kuwaitization',<br>disation',<br>'sau<br>'saudization',<br>worker'<br>'foreign<br>'bahrainisation',|
|_Liberalization_|sector','free<br>'private<br>reform',<br>'liberalis','liberaliz','privatis','privatiz','market<br>ivate'<br>pr<br>-<br>'public<br>regulation',<br>-<br>market','de<br>market','transparent|
|_Diversification_|'diversif','diverse','sustainable','sustainability'|
|_Financial_|direct<br>'foreign<br>'finance','financial','business','invest','capital','fdi',<br>system','hedge<br>sector','banking<br>market','ipo','banking<br>investment','stock<br>accounting','equity','equities'|
|_Labor_|'salaries'<br>'salary',<br>'fire',<br>'furlough',<br>'labor','labour','work','employ','job',|
|_Energy/oil_|'hydraulic',<br>'electric',<br>'electricity',<br>'water',<br>'barrel',<br>'oil','aramco','gasoline','fuel',<br>'energy'<br>'opec',<br>'petrol',<br>'aramco',|
|_World Bank/IMF_|fund','imf'<br>monetary<br>bank','international<br>'world|
|_Political_<br>_International_|'opposition',<br>'constitution',<br>'government','political','election','democra','defense',<br>'corrupt',<br>spring',<br>'arab<br>'crackdown',<br>'security',<br>'extremism',<br>'terror',<br>'protest',<br>'occupation'<br>'sectarian',<br>'parties',<br>'party',<br>'accountable',<br>'accountability',<br>'military',<br>'usa',<br>'afghanistan',<br>states',<br>'global','international','china','chinese','india','united<br>'iraq',<br>world',<br>'arab<br>east',<br>'middle<br>a','g20',<br>'foreign','yemen','iran','syri<br>'obama',<br>kingdom',<br>'united<br>'french',<br>'france',<br>'russia',<br>'egypt',<br>'palestine',<br>'lebanon',<br>'euro',<br>nations',<br>'united<br>un',<br>'the<br>'africa',<br>'brazil',<br>'sudan',<br>cooperation',<br>'gulf<br>'brit',<br>'uk',<br>''|
|_Social_<br>_Vision_|region<br>right'<br>'human<br>ucation','woman','women','youth','healthcare','school',<br>'social','ed<br>2030'<br>'vision|

41
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<!-- Start of picture text --> Reform Categories (Same Sentence) -- English Articles -- Social<br>0.40 -—— Oman — Qatar —— United Arab Emirates<br>035<br>§ —— Kuwait — SaudiArabia ~— Bahrain<br> 030<br>35 .<br>B 020 SZ,YS VAN Oo<br>z 015 NN Ld<br>3 0.10 jy WZ SS7<br> oo ZZ<br>0.00 ----nnannnnnnnnnnnnnnnnnnnnnnnnn nn ennnnn enn nn nnnnnnn nnnnncnnnncncennncccennccenns<br>se e se Year s 6° s<br><!-- End of picture text -->
<!-- Start of picture text --> Reform Categories (Same Sentence) -- English Articles -- Vision 2030<br>— Onan Oatar United Arab Emirates<br>8 0.20 — Kuwait —— SaudiArabia —— Bahrain<br>2<br><<br>€5 0.15<br>= 0.10<br>‘S<br>A<br>0,00 2H soeseas-----SaWt8.<br>se s scy Year sVv >& a<br><!-- End of picture text --> <!-- Start of picture text --> Reform Categories (Same Sentence) -- English Articles -- Trade<br>05 — Oman — Qatar — United Arab Emirates<br>3 —— Kuwait — Saudi Arabia ©— Bahrain<br>g<br>rs 04<br>2 03<br>z<br>8 . — ><<br>3 7 Ne<br>O.0 -n-a-n---=-- === non n nn nnn nnn nn nnn nnn nnn nnn nnn nn nnnnnn nnn nnn nn pnnnnnnnnnnnnnnsenes<br>se se se Year sVv #© #<br><!-- End of picture text --> <!-- Start of picture text --> Reform Categories (Same Sentence) -- English Articles -- Energy<br>05 ~~ Oman — Qatar —— United Arab Emirates<br>Pn —— Kuwait —— SaudiArabia =—— Bahrain<br>”<br>. IN<br>Bos<br>ZzE IN ‘a, \S<br>I Za BOKD °<br>Eon ONG DE<br>2 NY SS<br>0) -on enna nnn nn annem nnn nn nnn nnn nnn nnn nnn nnn nn nnn nnn nn nn nnn nnn nnn nnn nnn nn nc netene:<br>a se a Year SVv S© s<br><!-- End of picture text --> <!-- Start of picture text --> Reform Categories (Same Sentence) -- English Articles -- Diversification<br>0.200 —— Oman — Qatar — United Arab Emirates<br>0.175 —— Kuwait — SaudiArabia — Bahrain \<br>= 0.150<br>3 0.125 i: AY<br>3 NN VN<br>5 0.100 bX a =<br>3 \ YS<br>@ 0050 Xr,LIAAIRSAF<br>2 0.025 PY SS SE]<br>0.000 ------------------------------------------------------------------------------------5<br>se e se Year sv s© ss<br><!-- End of picture text --> <!-- Start of picture text --> Reform Categories (Same Sentence) - English Articles ~- Fiscal<br>04. — Oman —— Qatar United Arab Emirates<br>3;2 —— Kuwait —— SaudiArabia —— Bahrain<br>g3 J\ 7<br>3023 VAN<br>&S >< Pf<br>Bo" Nw > ft —D =<br>0.0 roe eS Tannen nnn nnn nnn nnn nnn nn ssn Sonn nnn nn nnn nnn nnn nnnnnnnen enn nn nnn n nnn tene:<br>s se se Year SsVv &© #©<br><!-- End of picture text --> <!-- Start of picture text --> Reform Categories (Same Sentence) -- English Articles -- Financial<br>05 — Oman — Qatar — United Arab Emirates<br>o<br>3eSS04503 — Kuwait — SaudiArabiaos QR—. Bahrain J_ASCEAis IN<br>305 VmVEN [>LLVUyj{/<br>58 02 AL4<br>Fo 7 VT<br>.<br>0.0 -----------------------------------------------------------------------------------2)<br>s s scy Year SsVv $scy spS<br><!-- End of picture text --> <!-- Start of picture text --> 08 Reform Categories (Same Sentence) -- English Articles -- International<br>2 o7“f — —— Kuwait Oman ——— SaudiArabiaQatar ———— UnitedBahrainArab Emirates<br>8 06 TS<br>5 05 <4pAFAS oNWASSe Z~<br>2 AV Wy <f<br>B83 Vv<br>BYg 02<br>201<br>00 ~---------------------------------------------------2 =n 2a nnnnnnnnnnnnnnnnnnnn nnn<br>* scy Year sVv S© Cy©<br><!-- End of picture text --> <!-- Start of picture text --> Reform Categories (Same Sentence) -- English Articles -- Labor<br>030 —— Oman — Qatar — _ United Arab Emirates<br>S3 0.25 — Kuwait —— SaudiArabia —— Bahrain<br>3: 020 ay) JLOd(\ yaLA |<br>5 01s LK A LEA Se<br>8 a, 7<br>N3 0.10 P<I Ky<\ > 7<br>5 0.05<br>0.00 renee n nanan nnnnnn nnnnn nnn nnnnnn nnnnnn nnnnn nnnnnn ennnn tance nen nn nn nenene:<br>* os Year sVv So Sy<br><!-- End of picture text -->

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# Appendix A6: Sentiment Analyses with News Media

Sentiment analysis refers to the task of extracting a text’s opinions, whether its general stance or its attitudes towards specific topics or persons. Natural language processing provides three general approaches for computing sentiment: 1) knowledge-based techniques, 2) statistical methods, and 3) hybrid approaches. Knowledge-based techniques categorize words with unambiguous effects, such as ‘good’ and ‘bad’ (Ortony et al., 1988). Statistical methods utilize techniques from machine learning, such as support vector machines and deep learning to classify sentiment (Turney 2002). Finally, hybrid approaches combine elements from the previous two.

In our analysis, we utilize knowledge-based techniques to compute and compare the sentiment of articles covering the GCC and its economic reforms. Specifically, we use the python package ‘polyglot’ for Arabic and English articles. The package provides extensive polarity lexicons—dictionaries classifying words as positive, negative, or neutral—in 136 languages, including Arabic and English. We calculate article k’s ‘support’ by taking the number of positive words minus the number of negative words, scaled by the total word count in the article: =<sup># RppRRppiittiivvRR wwRIIpp−# RIIRRppaattiivvRR wwRIIpp</sup> ppRRIIttiiR IItt<sup>kk</sup> In addition to measuring and analyzing overall sentiment, we also examined the most used charged ttRRttaavv # R wwR IIpp iiII tthRR aaRRttiissvvRR/IIRRssvvR IItt In addition to measuring and analyzing overall sentiment, we also examined the most used charged words—both positive and negative—to understand sentiment drivers. The most used positive words in English articles are similar across GCC countries, with ‘important’, ‘strong,’ ‘stable’, and ‘significant’ being most used. There are minor differences related to the relative frequency of specific words. Some examples include ‘stability’ being relatively larger in Oman, ‘ambitious’ for Saudi Arabia, and ‘sustainable’ for the UAE. However, the overall picture is similar. For the English articles, the most used negative word across most GCC countries is ‘crisis.’ There are notable cross-country differences in other major words. For instance, ‘opposition’ and ‘protests’ are the most used negative words in Bahrain, while ‘debt’ and ‘risk’ are major concerns in Oman, Kuwait, and the UAE. At the same time, Saudi Arabia sees heavier usage of ‘conservative’, ‘corruption’, and ‘terrorism.’ As observed when examining the most common words across the whole text in English articles, for the Arabic articles, the most used positive adjectives to describe reforms are similar across GCC countries. The most common adjectives are ‘new’, ‘wide’, ‘national’, ‘big’, ‘structural’, ‘deep’, ‘comprehensive’, and ‘legal.’ Minor differences include the word ‘competitive’ being relatively larger for articles on Oman, and ‘ambitious’ for those on Saudi Arabia.

45
# Appendix A7: Sentiment and FDI Inflows

The following section investigates the effect of international sentiment and discussions on FDI inflows to the GCC countries. The analysis is particularly important today as more and more GCC countries engage in reforms targeted toward improving FDI.

We perform our analysis using a panel of all six GCC countries over the period 2000-2020. We include a set of macroeconomic and structural variables in our estimation based on the existing literature. Data on GDP growth, inflation, FDI inflows, and trade openness are obtained from the World Development Indicators database; data on six institutional quality indices are obtained from the World Governance Indicators database.

Using the data described above, we estimate the following equation: R R The dependent variable in all specifications is FDI inflows as a percentage of lagged GDP. Our main FFDDIIiiIIRRvvRRwwppii,tt = ααii + ββtt + λλR λλRRIIiiaaii,tt + XXii,tt + εεii,tt variables of interest are a group of reform media variables (international reform chatter, international reform sentiment, Twitter reform intensity, and Twitter reform sentiment). Each of these variables is standardized to have zero mean and unit variance in the regression. The construction of these variables is described in the main text. In addition, we control for GDP growth, inflation, trade openness, and institutional quality in all regressions. We consider the latter to be a good proxy for the attractiveness of a country for FDI investors. Finally, we include country and time fixed effects—the former control for unobserved, country-specific, and time-invariant differences in FDI attractiveness across the GCC countries. Time fixed effects capture the effects of any large shocks (e.g., Global Financial Crisis, Arab Spring) on FDI attractiveness across all countries.

Our main results on FDI inflows using news media are presented in Table A7.1. The results from Column 3 suggest that sentiment about GCC economic reforms in international media is significantly and robustly correlated with the level of FDI inflows. Moreover, the size of this effect is economically significant: one standard deviation increase in reform sentiment is associated with a 0.9 percentage point increase in FDI inflows or a 34% increase from the mean level of FDI inflows. This finding suggests that support for current reforms matters for FDI. Put differently, ‘talk is not cheap’. Interestingly, international reform chatter and the interaction between chatter and sentiment are not significantly associated with FDI inflows.

Table A7.2 presents a complimentary analysis of the effects of Twitter reform intensity and sentiment on FDI inflows. The results are very similar to those in Table A7.1, confirming the important influence of media tone on investment behavior. The coefficient on Twitter reform sentiment suggests that a one standard deviation increase in tone is associated with a 0.4 percentage point increase in FDI inflows or a 23% increase from the mean.

46
# **Table A7.1 International Reform Sentiment and FDI Inflows into the GCC**

|Dependent Variable:|FDI In|flows (% of lagged|GDP)|
|---|---|---|---|
|Int'l Chatter (t)|-0.0463||-0.704|
||(0.423)||(0.488)|
|Int'l Sentiment (t)|0.965<sup>**</sup>||0.989<sup>***</sup>|
||(0.322)||(0.227)|
|Int'l Chatter * Int'l Sentiment (t)|0.0740||-0.153|
||(0.287)||(0.251)|
|Int'l Chatter (t-1)||0.978|1.381<sup>*</sup>|
|||(0.719)|(0.675)|
|Int'l Sentiment (t-1)||0.785|0.390|
|||(0.508)|(0.378)|
|Int'l Chatter * Int'l Sentiment (t-1)||0.505|0.484|
|||(0.358)|(0.362)|
|GDP Growth (t)|0.115|0.141<sup>***</sup>|0.109<sup>**</sup>|
||(0.0581)|(0.0197)|(0.0348)|
|Inflation Rate (t)|0.0226|-0.0174|-0.00993|
||(0.175)|(0.127)|(0.123)|
|Trade Openness (t)|0.107<sup>**</sup>|0.106<sup>**</sup>|0.106<sup>*</sup>|
||(0.0413)|(0.0331)|(0.0443)|
|Institutional Quality (t)|0.724|-1.534|-0.407|
||(3.495)|(2.454)|(2.291)|
|Country FE||||
|Year FE||||
|R2|0.605|0.622|0.655|
|Mean of Dependent Variable|2.858|2.899|2.899|
|Number of Countries|6|6|6|
|Observations|103|100|100|

Note: This table presents the relationship between GCC reform chatter and reform sentiment in non-GCC international media and FDI net inflows to the GCC. Coverage includes the six GCC countries between 2000 to 2020. Reform discussion and reform sentiment are in both English and Arabic and normalized to have unit variance. Trade openness is measured as the value of exports plus imports as a percentage of GDP. Institutional quality is the average of six measures from the World Governance Indicators database. Standard errors are clustered at the country level and papered in parentheses.<sup>*</sup> _p_ < 0.10,<sup>**</sup> _p_ < 0.05,<sup>***</sup> _p_ < 0.01 47
**Table A7.2 Twitter Reform Sentiment and Intensity and FDI Inflows into the GCC**

|Dependent Variable:|FDI Inflows (% of GDP)|
|---|---|
|Twitter Reform Intensity (t)|-0.222<br>(0.665)<br>|
|Twitter Reform Sentiment (t)|0.403<sup>**</sup>|
||(0.119)|
|Twitter Reform Intensity X Sentiment (t)|-0.894<br>(0.597)|
|Twitter Reform Intensity (t-1)|-1.479|
||(1.082)|
|Twitter Reform Sentiment (t-1)|-0.478|
||(0.543)|
|Twitter Reform Intensity X Sentiment (t-1)|0.647|
||(0.765)|
|GDP Growth (t)|0.0816|
||(0.137)|
|Inflation Rate (t)|0.437|
||(0.292)|
|Trade Openness (t)|0.0930|
||(0.0685)|
|Institutional Quality (t)|0.628|
||(3.686)|
|Country FE||
|Year FE||
|R2|0.663|
|Mean of Dependent Variable|1.753|
|Number of Countries|6|
|Observations|46|

Note: This table presents the relationship between GCC Twitter reform intensity and reform sentiment and FDI net inflows to the GCC. Coverage includes the six GCC countries between 2011 to 2019. Twitter intensity and sentiment are derived from Arabic tweets, and the measures are normalized to have unit variance. Trade openness is measured as the value of exports plus imports as a percentage of GDP. Institutional quality is the average of six measures from the World Governance Indicators database. Standard errors are clustered at the country level and papered in parentheses.<sup>*</sup> _p_ < 0.10,<sup>**</sup> _p_ < 0.05,<sup>***</sup> _p_ < 0.01 48