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    Home » Archives for Mineka » Page 14

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    An Analysis Into The Reasonings Behind The Macroeconomic Fluctuations In Sri Lanka’s Post Covid Economy

    July 22, 2024 No Comments

    An Analysis Into The Reasonings Behind The Macroeconomic Fluctuations In Sri Lanka’s Post Covid Economy

    The post-Covid Era signals the period that follows the socioeconomic turmoil caused by the COVID-19 pandemic during which economies start to recover and life sets into pre-Covid normalities (WHO, 2021). In Sri Lanka this period is evident following the last economic quarter of 2021 during which the nation unfortunately faced its deepest economic and political crisis triggered mostly by federal economic mismanagement. The following report is therefore centred on economically examining the gravity of this crisis in terms of fluctuating macroeconomic indicators and have their reasons expressed using hypothetical economic models. The report ends with a statistically-proven argument on which macroeconomic objective could have been prioritised in order to optimise success and circumvent calamity.

    EVIDENCE OF CHANGES

    ANALYSIS OF CHANGES

    The fluctuations between the quarters for each indicator can be understood through autonomous reasonings illustrated through hypothetical shifts in aggregate supply or demand.

    The post-Covid era has seen severe variability in the unemployment rate with more individuals being laid-off than the natural rate. Industrial experts suggests that post-Covid unemployment is linked with the high prices of imported production inputs due to the high taxes levied on them by the government to battle foreign-exchange shortages. In-fact, this is evident in the national construction industry where 90% of projects are kept on standstill due to insufficient raw materials.

    The AD-AS model can aid our understanding of this scenario as government restrictions and taxes have increased production costs thus shifting the SRAS curve to the left causing more workers to get unemployed due to the reduction in production activities by firms as the Real GDP level (Y1) inches further away from full employment at YF.

    Economic growth on the other hand has continued to decline and set the nation on a prolonged recession. The government has stated that this contraction was stimulated by high unemployment combined with inflationary pressure that reduced real incomes and curtailed consumer spending. Furthermore, higher interest rates raised borrowing costs and thus dwindled investments by firms and governments to spend more cautiously. As a result, overall spending decreases shrinking financial returns on firms and creating a cyclical cycle of economic declines.

    Once again, the AS-AD model vividly exemplifies this scenario with the AD curve shirking to the left representing the reduction in consumer, investment and government spending resulting in an indisputable decrease in Real GDP. This is equivalent to an economic downturn on the economic cycle as it approaches a trough.

    Inflation has played a significant role in Sri Lanka’s economic turmoil and has continually increased during the post-Covid era. At a glance, the reasonings behind this can be exemplified by the disruptions caused in global supply chains due to the energy and food crisis caused by the Ukrainian conflict causing import restrictions and higher tax rates. One key change took place with a policy change in 2021 to shift from chemical to organic fertilizers overnight due to forex shortages that entirely disrupted Sri Lanka’s food supply.

    According to AS-AD model this policy created a supply shock in the agricultural industry that resulted in essential food products like fresh produce being extremely scarce thus raising their prices. This is an application of cost push inflation but paired with the effect of reduced unemployment this could be classified as stagflation. As a result, the entire aggregate-supply curve would have shifted to the left resulting in the severe inflationary pressures Sri Lanka saw in 2022.

    Poor external stability is at the core of Sri Lanka’s economic turmoil with foreign debt accumulating a great share of GDP. This is because Sri Lanka has historically imported and borrowed more than what it has earned through exports with tourism revenue greatly falling due to the pandemic. In addition, the poor expansionary policies of the government back in 2019 which included low interest rates and taxes would have further pushed import spendings and drained more foreign reserves. Gradually as Sri Lanka hit the economic turmoil of 2022, foreign reserves were at an absolute minimum causing countless other decisions to be made so the government can pay its current and past debt obligations and spend on essential imports reducing Sri Lanka’s external stability. While in-crisis, the government chose to borrow more in the form of currency swaps and loans from neighbouring countries which further increase the debt-to-GDP ratio.

    STATISTICAL INTERCONNECTEDNESS BETWEEN INIDATORS AND CONCLUSION

    A recurring reason behind the economic calamity that Sri Lanka faced in 2022 as mentioned multiple times in this analysis is the falling forex reserves which shows a sharp decline over the post-Covid period correlating well with the worsening trends of other indicators like economic growth, unemployment and inflation. Forex reserves like debt ratios signify a nation’s external stability as it acts as a liquid asset representing the confidence and ease at which a nation can repay its debt obligations and procure essential imports and raw materials for production and consumption activities.

    Due to mismanagement and faulty policies, Sri Lanka has indisputably grappled a forex shortage throughout this period which is why firms had to close down production processes due to insufficient inputs contracting the economy with a variation of 78.8% explicable through this phenomenon as evident through regression analysis.

    Economic contraction (GDP Degrowth) and falling production levels have simultaneously led to high unemployment with 70.4% of the variation in unemployment explicable through the variation in GDP degrowth. This was because as aggregate supply fell alongside lower spending levels meaning firms had to lay-off workers to compensate the loss in production requirements.

    Finally, as the effect of reducing aggregate supply outweighed the decline aggregate demand and workers were laid-off a stagflation like situation was created with a strong 98% of the variation in inflation rates explicable by the economic contraction meaning as the economy contracted, workers were laid-off while firms struggled to produce further prices were put up by firms in order to battles the shortage of goods the country faced.

    The above visualisations as reported through the outcomes of regression analysis narrates the story of Sri Lanka’s post covid economic disaster met further with political instability, civilian unrest and increased relative poverty and interconnectedness of various macroeconomic indicators with the initial core reason centred on falling forex reserves. This highlights how Sri Lanka’s inability to manage its external stability is what drove the economic crisis and could have been prioritised form the start in order to avoid this economic calamity.

    To counter argue, if Sri Lanka were to prioritise on another objective, say economic growth and reducing unemployment by introducing progressive expansionary policies, firms and consumers would further spend their pockets on imported goods and raw-materials further plummeting forex reserves until they are drained to the extent Sri Lanka may have to declare a full bankruptcy and loose its capability of being a full-functional country.

    Therefore, it is indisputable that prioritising external stability as a macroeconomic objective particularly with the availability of forex reserves is crucial particularly in countries like Sri Lanka which depend heavily on foreign debt and essential imports as any shortage can results in essential goods being unavailable within the economy that leads to economic contraction, higher unemployment and poor price stability as illustrated in the case of Sri Lanka.

    References

    Macroeconomic Chart Pack: Central Bank of Sri Lanka (no date) Macroeconomic Chart Pack | Central Bank of Sri Lanka. Economics Research Department. Available at: https://www.cbsl.gov.lk/en/statistics/economic-indicators/macro-economic-chart-pack (Accessed: April 2, 2023).

    What is post-covid-19 era (no date) IGI Global. Available at: https://www.igi-global.com/dictionary/post-covid-19-era/99484 (Accessed: April 1, 2023).

    Sri Lanka Foreign Exchange reserves march 2023 data – 2004-2022 historical (no date) Sri Lanka Foreign Exchange Reserves – March 2023 Data – 2004-2022 Historical. Central Bank of Sri Lanka. Available at: https://tradingeconomics.com/sri-lanka/foreign-exchange-reserves?embed%2Fforecast (Accessed: April 2, 2023).

    What is post-covid-19 era? – WHO (no date) IGI Global. Available at: https://www.igi-global.com/dictionary/post-covid-19-era/99484 (Accessed: March 29, 2023).

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    My Writing Corner Pulse of the World

    Transformative Trends: New Developments Powering The Sustainable Investing Landscape Down Under

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    Transformative Trends: New Developments Powering The Sustainable Investing Landscape Down Under

    The 2024 investment landscape of Australia is a product of a multitude of transformative factors, including technological advancements, regulatory conditions, and geopolitical tensions. For investors aiming to capitalise on the untapped opportunities within Australia’s financial markets, a comprehensive understanding of these factors is crucial. According to numerous independent analysts, one trend anticipated to expand in 2024 is sustainable investing, a sector that has recently evolved from a niche to a mainstream market, compelling companies to adopt ESG-oriented policies and decisions that cater to investor demands. Parallel to this trend is the evolving definition of sustainable investing which previously entailed merely investing in companies with strong ESG credentials but encompasses a more holistic approach (Comendador, 2024). Today, investors prioritise organisations with potential rather than just past achievements and are more inclined to scrutinize ESG data in detail before making investment decisions. The following article deconstructs and analyses the key developments shaping Australia’s sustainable investment landscape in 2024, focusing specific attention towards enhanced ESG regulation, the power of generative AI, and calls for a more practical finance education.

    Launching the Sustainable Finance Roadmap

    The Sustainable Finance Roadmap was a proposal that was previously formulated by the Australian Sustainable Finance Initiative (ASFI) in November 2020 and was focused on transforming the country’s financial systems and markets in a way that helps mobilise funds towards the nation’s growing sustainability needs while also maintaining consistency with global sustainability agendas like the Paris Agreement or the UN’s SDGs (ASFI, 2020). In June 2024, the Australian Government released an updated version of the Sustainable Finance Roadmap, which continues to emphasise the importance of sustainable finance reforms with key priorities including instituting mandatory climate-relating reporting, establishing a sustainable finance taxonomy, and instituting a labelling regime for sustainable investments.

    One crucial insight from the road map is the emphasis placed on the Australia Accounting Standards Board (AASB) to finalise its climate reporting standards and disclosures by August 2024 such that they can be implemented on a test group of companies form January 2025 onwards before it is mandated through corporate legislation across all Australian firms that bear public accountability (Segal, 2024). In addition to this, emphasis has also been placed on developing a Sustainable Finance Taxonomy which would provide investors and corporations with a definite set of criteria and algorithms to evaluate a project’s ESG impact and its alignment with global and national sustainability objectives. Through this development the government has also proposed a mandatory labelling system that seeks to flag financial products and instruments according to their sustainability impact that would help streamline the process of selecting investments.

    According to the Australian Treasurer, Jim Chalmers, the Roadmap is a crucial framework that would help responsible investors make better and more streamlined decisions regarding sustainable investment thus enhancing the mobilisation of private capital from investors to the nation’s green endeavours with particular emphasis on the renewable energy transformation that aligns well with Australia’s Net Zero goals (Segal, 2024).  Moreover, the roadmap is a crucial element to modernising and reducing the inefficiencies inherent in capital markets like asymmetric information. Through mandatory disclosures, formal labelling systems and algorithmic methods developed at the hands of the government, sustainable investors will be devoid from the impacts of ingenuine reporting and unequally shared information which can be now tracked and reported through the legal system. These regulatory changes once implemented will create a new generation of responsible investors who are better capable of mobilising their capital towards productive investments that generate both economic and socio-environmental returns that cater to Australia’s sustainability interests.

    Harnessing the Power of Generative AI

    Unlike regulatory enforcements and frameworks, one change that is unanimously evolving the global commercial landscape is Generative AI and Australian investors are no exception to harnessing the advanced capabilities that this technology posits in the realm of sustainable investing (Comendador, 2024). Generative AI is a technology born out of advanced machine learning models and neural networks which thereby instil its capabilities in generating human content and mimicking human creativity. IntellectAI is one such tool that has grown in popularity among Australian investors which helps consolidate unstructured ESG data into structured datasets that can be used to derive meaningful insights and perform better sustainability analysis (Jhaxel, 2024). According to the developers of these tools, incorporating AI into ESG analysis enhances data precision and could help investors isolate and identify the most productive sustainable investments.

    Tim Mohin, a director at the Boston Consulting Group, states that 40% of the world’s GDP is contingent upon mandatory climate and ESG disclosure as regulatory requirements are reinforced amongst nations similar to Australia’s formalisation of the Sustainable Finance Roadmap (Kell, 2024). One argument posits that this rise in regulation would subsequently drive the market for AI tools that enhances a firm’s ESG tracking mechanisms as tools available at the disposal of investors.  One insightful application of AI that would help investors is the detection of washing techniques (eg: greenwashing, pinkwashing) which can be collectively defined as a form of asymmetric information that misleads investors on a corporation’s environmental and social agendas. As these techniques threaten the credibility of sustainability, Generative AI tools can be utilised in uncovering such techniques ensuring investors make well-informed decisions that re devoid from washing. One recent development involved, EY, a prominent auditing and assurance firm, collaborating with several start-ups in designing a “Greenwashing Compass” that allows firms to screen descriptive narratives on their sustainability narratives to detect the likelihood of it being perceived as greenwashing by a human reader (Torsvik, Ellingsen &Vinge, 2023).

    Despite the increasing integration of artificial intelligence (AI) into sustainable investing, notable weaknesses and concerns persist that merit careful consideration. A primary issue is the substantial energy consumption of AI-driven data centres, which raises significant sustainability concerns. Tim Mohin from Boston Consulting Group highlights this challenge by noting, “Data centres continue to consume an outsize portion of energy”, a situation that threatens to undermine the very sustainability objectives these technologies are intended to support (Kell, 2024). This paradox of high energy consumption potentially counteracting sustainability goals presents a serious dilemma. Additionally, there are ongoing doubts about the reliability and quality of AI-generated Environmental, Social, and Governance (ESG) analyses. John Friedman, an expert in ESG strategy, stresses the importance of rigorous validation and human oversight to ensure that AI outputs are accurate and dependable. He cautions that investors and companies should not rely solely on AI results without comprehensive testing and validation, underscoring the need for continuous evaluation of AI models with diverse datasets to maintain the integrity of sustainable investment decisions. Addressing these concerns is crucial to ensuring that the advancements in AI within the realm of sustainable investing do not compromise the reliability and efficacy of investment insights.

    Educative Developments in Sustainable Investing

    As of 2024, Australia is among the world leaders in educating its youth regarding sustainability and how corporations can be part of this global challenge. This is characterised by the numerous discovery courses that are available to commencing students at university and the many collaborations, projects and competitions that are held amongst schools that bear sustainability as a central focus. Recently, the Responsible Investment Association Australasia (RIAA) also announced its intentions on launching an adviser-focused course next month about integrating ESG into investing. According to preliminary details, the course centres on equipping professional investors with the skills to leverage technology such as Generative AI in their sustainability assessments while also training them to respond to company policies by rebalancing their portfolio (Siljic, 2024). While programs like these characterise Australia’s growing sustainable investing sector while predicting further growth opportunities in coming years, question remain on whether the nation’s doing enough to educate its student population on sustainable investing.

    One article authored by Lorin Busaan, a PhD student, and Basma Majerbi, an Associate Professor of Finance at the Gustavson School of Business, University of Victoria, highlights a significant gap in current finance education in Australia regarding sustainable investments which in order to mitigate requires the unanimous attention of Australia’s leading higher-education institutions. In their article, they describe the system of Canadian SMIFs which serve as educational platforms that simulate an environment in which student must manage real investment portfolios which can be adjusted in ways that ESG criteria into account (Busaan & Majerbi, 2024). The authors underscore that its is innovations like these that bridge the gap between financial theory and practice are crucial to addressing the education gap in Australian tertiary sector. They posit that when simulation technologies like SMIFs are adequately adopted to financial majors, student will be better instilled with capabilities and skills to address sustainability challenges like carbon emissions and social inequality as both managers and investors. Therefore, the article’s stress the need for business schools to revise their finance curricula to include robust training in sustainable investing. This includes not only theoretical understanding but also practical experience integrating ESG criteria into investment analysis and decision-making.

    Ultimately there are certainly educative developments pertaining to sustainable investing that are present at secondary, tertiary and professional level in Australia such as introductory courses that introduce students to the interactions between commercial disciplines and sustainability challenges as well as professional courses that equip responsible investors with skills to leverage AI in investing sustainability. However, despite these courses, as expert evidence evinces, a tertiary education gap persists in Australia’s finance education that does not allow its graduates to replicate theory into practical settings especially those that require the analysis and synthesisation of ESG data. As the article above proclaims, lessons from Canada’s SMIF system can be incorporated to current finance courses in order to enhance student’s performance as both a responsible financial manager and investor. These enhancements, if embraced by Australia’s business schools would help better unlock the stocks of private capital that could be mobilised into projects focused on achieving Net Zero objectives such as the renewable energy sector transformation and ultimately drive sustainable investing in future years.

    Conclusion

    In conclusion, the investment landscape in Australia for 2024 is shaped by significant transformative factors including technological advancements, regulatory developments, and global pressures. Sustainable investing stands out as a pivotal trend, evolving from a niche interest to a mainstream priority. The updated Sustainable Finance Roadmap and advancements in generative AI are poised to reshape how investors approach ESG considerations, enhancing transparency and efficiency in sustainable investment decisions. Educational initiatives are also crucial, yet there remains a notable gap in integrating practical sustainable investing skills into finance education at all levels.

    To address these challenges effectively, Australian business schools must urgently adapt their curricula to incorporate robust training in sustainable finance. This includes leveraging simulation technologies and practical experiences like those seen in Canadian SMIFs to equip students with the skills needed to navigate complex ESG landscapes. By doing so, Australia can foster a new generation of finance professionals capable of steering investments towards both economic prosperity and sustainable impact, thus driving forward the nation’s aspirations for a greener, more resilient future.

    REFERENCES

    Australian Sustainable Finance Initiative, (ASFI). (2020) Australian Sustainable Finance Roadmap (2020): A plan for aligning Australia’s financial system with a sustainable, resilient and prosperous future for all Australians Acknowledgement of Country.https://static1.squarespace.com/static/6182172c8c1fdb1d7425fd0d/t/6240de97b51f1159dbc20e24/1648418477411/FINAL+Australian+Sustainable+Finance+Roadmap+%28mobile+version%29+%28Embargoed+until+24+November%29.pdf

    Busaan, L. & Majerbi, B. (2023, August 27) Business schools must step up on sustainable investing education. (2023, August 27). The Conversation. https://theconversation.com/business-schools-must-step-up-on-sustainable-investing-education-208352

    Comendador, N. (2024, May 26). The future of investment: Trends shaping Australia in 2024. Www.nestegg.com.au. https://www.nestegg.com.au/invest-money/investment-insights/the-future-of-investment-trends-shaping-australia-in-2024

    Jhaxell. (2024, June 13). How Generative AI transforms ESG data into sustainable investment success. FinTech Global. https://fintech.global/2024/06/13/how-generative-ai-transforms-esg-data-into-sustainable-investment-success/

    Kell, J. (2024, March 27). How AI can boost sustainable investing. Fortune. Retrieved July 19, 2024, from https://fortune.com/2024/03/26/smart-strategies-ai-investing-sustainability/

    Segal, M. (2024, June 20). Australia Launches Plans for Mandatory Climate Reporting, Taxonomy, Sustainable Investment Labels. ESG Today. https://www.esgtoday.com/australia-launches-plans-for-mandatory-climate-reporting-taxonomy-sustainable-investment-labels/

    Siljic, J. (2024, June 27.). RIAA to launch sustainable investing course for advisers | Money Management. Www.moneymanagement.com.au. Retrieved July 19, 2024, https://www.moneymanagement.com.au/news/financial-planning/riaa-launch-sustainable-investing-course-advisers

    Torsvik, V., Ellingsen, S. & Vinge, E. (2023, October 3). Can artificial intelligence uncover greenwashing? EY. https://www.ey.com/en_no/digital/can-artificial-intelligence-uncover-greenwashing‌

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    My Writing Corner Pulse of the World

    The $450m Painting? : Interactions and Incongruences between Market Values and Artistic Values in Art Auctions

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    The $450m Painting? : Interactions and Incongruences between Market Values and Artistic Values in Art Auctions

    Unlike traditional investments like shares or bonds, whose prices reflect the discounted net economic benefits expected over an observable future, valuing artistic endeavours is often perceived as complex task that is usually left to the judgment of historians and art experts. The fundamental problem of determining the monetary value of art cyclically resurfaces during auctions of renowned artworks. For instance, in the Autumn of 2017, Christie’s held a historic auction of Da Vinci’s “Salvator Mundi,” which sold for an astronomical US$450.3 million, the highest price paid for an artwork since Picasso’s “Woman of Algiers” in 2015 (Freeman, 2017). As news of the auction spread across global communication channels, questions arose from academics in various disciplines whose inquiries were later compiled into the 2021 documentary titled “The Lost Leonardo.”

    What factors play into the fair value determination of a historic artwork? How does the economics of auction markets justify the staggering price tag of the “Salvator Mundi”? Can contemporary market theory be applied to art auctions, and can formulaic approaches assist in the valuation of art? This article, part of a three-part series, and in the context of the “Salvator Mundi” auction, systematically analyses the first of these questions on what factors play in the price determination of an artwork with specific focus on artistic and market values interact with each other. Together, both articles attempt to redefine our contemporary comprehension of arts auctions and cumulatively assess the extent to which the “Salvador Mundi” fits it exorbitant price tag.

    What factors play into the fair value determination of historic artwork?

    Before answering this question, it is important to make a crucial distinction between what constitutes as artistic value and market value. Predominantly artistic value is a reflection of the intrinsic worth of an artwork based on a broad range of subjective factors at the discretion of its critics like its cultural significance, emotional impact and critical acclamation while market value is based on observable and objective economic forces like the artwork’s scarcity and market dynamics usually accounted through a monetary figure. Intuitively the market value of an artwork is contingent upon its artistic value and at times these values maybe at disequilibrium although there is now a growing consensus that the two share a bidirectional relationship (Blum, 2021). In the context of Salvador Mundi for example, its fair value was predominantly derived from its association to Leonardo Da Vinci himself whose feats in multi-faceted disciplinary areas still remain a revered endeavour thus increasing the painting’s market value. Conversely, the market value of the Salvador Mundi as decided by the auction market at $450 million triggered artistic debates and renewed scholarly interests regarding the secrets and provenance of the painting which consequently increased its artistic value. This bidirectional relationship is one that is crucial to understanding the economics of arts markets, although frequent debates emerge regarding which value should systematically have a greater influence over the price of an artwork.

    One interesting proposition was developed through research published by the University of Melbourne’s Arts faculty concluded that the increasing commercialisation of art coupled by overpowering salesmanship and dynamic market forces is reshaping the arts market such that the artistic value of an artwork is overshadowed by its market counterpart. This tendency tends to discriminate against the artist’s merit which calls for the innovation of methods and mechanisms that while persevering the intrinsic cultural and emotional significance of artworks allows the market value of an artwork to operate (Zhang, 2022).

    Through a business-oriented lens, the outcome of Christie’s record-breaking $450.8 million auction is one that encapsulates how increasing commercialisation has led to market values overpowering artistic values in a way that exorbitant prices like this maybe a negative reflection of the artworks intrinsic worth. At first glance, it is feasible to state that the price was a result of the heightened competition among buyers to procure the scarce, one-of-a-kind artwork but extending beyond this argument we realise that marketing and branding in addition to prior ownership of the painting played a significant role in its final price determination. Christie’s compelling branding of the painting as the “Lost Leonardo” generated immense hype and anticipation which led to an associated media frenzy which may have overshadowed the painting’s intrinsic artistic qualities. Similarly, the artwork rocky past of having being owned by controversial figures could have also led to its grand price tag likewise overshadowing its artistic value. These figures with Charles I of England, Swiss dealer Yves Bouvier and Russian oligarch Dmitry Rybolovlev where the latter two were involved in a fierce legal dispute over the market price at which the painting was sold. Like previously stated the influx of market factors is what desecrates and debilitates the intrinsic artistic value of a painting which given the disputed provenance, cultural impact and authentic of the painting could potentially mean that the artistic value of the Salvador Mundi was significantly less that what was reflected through superficial market prices (Kjaer, 2021).

    Despite the objectivity of market value over artistic value, the previous passages indicate its inefficacy of determining a ‘real’ price for an artwork just as imperfect capital and product markets today may understate or overstate the values of investments and commodities respectively. As described in the previously mentioned research, independent arts valuators are those responsible for assessing the intrinsic value of art before they allow markets to decide its final price. Art valuators assess artworks based on factors such as cultural and emotional significance, as well as technical attributes like colour and authenticity. They consider the artwork’s historical context, its impact on culture, and its ability to evoke emotional responses from viewers, recognizing these elements as core to its artistic value. In addition, valuators employ modern scientific visual examination techniques to analyse the physical properties of the artwork. These techniques include infrared reflectography, X-ray fluorescence, and pigment analysis, which help determine the authenticity, condition, and original colours of the piece. By combining these scientific methods with an understanding of the artwork’s cultural and emotional importance, valuators can provide a comprehensive assessment of its true artistic value.

    Conclusion

    In summarising the current insights, it is evident that artistic value and market value maintain a reciprocal relationship. However, commercial influences such as marketing, media, and supply and demand dynamics often cause market value to overshadow artistic merit. This trend is notably observed in art auctions like the 2017 sale of the Salvador Mundi. Buyers frequently prioritize superficial factors shaped by commercial environments—such as brand prestige and previous ownership—over the intrinsic qualities of the artwork when determining their purchasing decisions. Conversely, assessments conducted by art appraisers tend to offer a more accurate reflection of an artwork’s true value. These evaluations take into account cultural significance, historical context, and aesthetic appeal, factors which contribute to the artwork’s worth. Despite their subjective nature, such appraisals are generally regarded as providing a clearer assessment of value compared to market metrics. Looking forward, advancements in technology are expected to enhance the precision of art valuation processes, potentially making artistic value more objective and comparable to market indicators. This alignment would contribute to a more balanced consideration of both artistic and commercial aspects in the valuation of artworks.

    REFERENCES

    Blum, M. (2021, July 9). Auction mechanisms and the formation of prices in the art market. Theses.Hal. Science. https://theses.hal.science/tel-03648839/

    Freeman, N., & Freeman, N. (2017, November 16). Leonardo da Vinci’s “Salvator Mundi” Sells for $450.3 M. at Christie’s in New York, Shattering Market Records. ARTnews.com. https://www.artnews.com/art-news/news/leonardo-da-vincis-salvator-mundi-sells-450-3-m-christies-new-york-9334/

    Leonardo da Vinci’s “Salvator Mundi” | 2017 World Auction Record | Christie’s. (n.d.). Www.youtube.com. Retrieved July 27, 2021, from https://www.youtube.com/watch?v=3orkmMlSpmI

    Kjaer, H. (Director). (2021). The lost Leonardo [Documentary]. Art Documentary Productions.

    Zhang, X. (2022) The Value of Arts and Its Force: The Artistic Value and the Art Market, 638(1). https://www.atlantis-press.com/proceedings/icpahd-21/125969473

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    Which Big 5 Personality traits do Sri Lankan leaders predominantly share?

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    WHICH BIG FIVE PERSONALITY TRAITS DO SRI LANKAN LEADERS PREDOMINANTLY SHARE AND VARY?

     

    ABSTRACT

    Leadership is described as a skill rather than a trait which could potentially elevate a person’s pathway in life. However, to achieve leadership qualities specific traits maybe ideal in specific intensities which may vary or be static between leadership personalities. The following report conveys a research question investigated by a student of Gateway College, Colombo for an academic folio. The question investigated is on whether leaders share similar scores in the trait spectrums of the Five Factor Model (FFM) and how they could potentially vary. The report is structured conventionally starting from the background profile, academic aims and research design description that includes both the procedural algorithm and sampling methods used. It then proceeds to give an in- depth display and analysis of the results of this study through both descriptive statistics and data visualisations summarising the critical data patterns observed among the variables of this study. The report ends with well-rounded conclusion(s) and its(their) relevant evaluations alongside further suggestions for future research in the field of leadership and trait psychology.

    BACKGROUND PROFILE

    When considering the background of this study I chose to write on why this study became an area of interest as well as a brief introduction to technical subject matter and jargon that this study deals with such as conceptions of trait psychology in general and the nature of the Five Factor Model (FFM).

    LEADER’S AND THEIR TRAITS

    Academics say leadership has never been a fixed attribute within our personality but is quality formulated through a network of traits (Gibbs, 1947). While there are some traits that drastically vary between leadership personalities, there are others that are roughly similar in terms of score. In fact, this statement is supported by prior research evidence which suggests that while certain traits may apply universally among ideal leaders, most traits could distinctly vary (Kirkpatrick, 1991). I believe that stating their dissimilarity is discernible so what drew my ardour towards this area was finding exactly which of these traits vary and which of them coincide similarly. In order to maintain credibility and standardisation I chose to use the Five Factor Model or BIG 5 test as commonly called to define its traits as variables.

    THE BIG FIVE TEST (FIVE FACTOR MODEL)

    According to most trait theorists, The Five Factor Model (FFM) is now constituted as a basis of most personality structures (Pervin, 2009) which makes it an appropriate model to decompose the variables of a leadership personality. The model factors personality into five different dimensions:  extraversion, agreeableness, conscientiousness, neuroticism and openness (Costa & McCrae, 1992). Openness is an intra-psychic trait which describes our willingness to change (Costa & McCrae, 1992) where high scorers are usually those that appreciate a dynamic and unpredictable lifestyle. Meanwhile conscientiousness describes our propensity to be self-controlled, hardworking and responsible (Jackson & Roberts, 2017). Extraversion on the other hand tells how energised we are in the presence of people and consists of several individual factors like sociability and impulsivity (Eaves & Eysenck, 1975). A low scorer in this spectrum would be described as introvert and would therefore be less energised in social gatherings. The fourth trait, agreeableness refers to a person’s disposition of being likeable, pleasant and harmonious with others (Graziano & Tobin, 2009) and finally neuroticism which reflects our response and stability to environmental stress where high scorers are vulnerable to feelings like guilt and dejection. (Widiger, 2009).

    A strong feature of the BIG 5 test, apart from the fact that it can be conducted cost-effectively in a virtual environment, is that it uses an established content analysis procedure to give a quantitative score for each trait (together known as an OCEAN score) meaning that the gathered data can be immediately visualised on charts and set for statistical testing. This makes it a scientific instrument, which, moreover, has a high degree of reliability and validity as shown through studies (Thiel, 2021).

    OBJECTIVE OF THE STUDY

    Throughout this investigation, my aim is to understand whether leadership personalities irrespective of their gender, position or role encompass certain BIG 5 traits that vary drastically between personality to personality alongside other traits that remain relatively constant. By researching this question, individuals can understand the traits that may enhance and the traits that would not inhibit their ability to take up effective leadership representing a good use of science been utilised as a human endeavour. For instance, if introversion drastically varies amongst successful leaders, an introvert desiring to take up leadership may understand that his/her introversion is not a deterrent to his capability of becoming a strong leader. Meanwhile if conscientiousness is a quality that remains constantly high across most leader, a laid-back person may understand that he/she ought to have the propensity to be hardworking, astute and goal-oriented in the future to take up leadership. Hence this study can offer qualitative advice and applicative use to many stakeholders especially those beginning to approach leadership which hence becomes an external objective of this study.


    RESEARCH DESIGN

    To investigate the titled research question, an observational research design seemed appropriate whereby we hand over the official BIG 5 online survey to each of the participants and compare their OCEAN scores statistically to identify which ones are shares and varied. The following flow chart functions as an algorithm that summarises the research procedure.

    METHODOLOGY

    The investigation starts by sampling leaders and gaining their consent in a recursive pattern (see below) and then proceeds to give the official BIG 5 personality test available at www.truity.com/test/big-five-personality-test. Afterwards participants refill the five scores and other details like age and leadership roles in an independent form. Following the data gathering stage, the results will be prepared on a spreadsheet where a descriptive statistical test is to be performed followed by displaying a series of data visualisations which can then be used to gain insights into the question, formulate findings and lastly write a conclusion.

    Figure 1: Flow chart that summarise research method and process visually.

    A critical part of procedure is highlighted in the decision box in Figure 1 involves gaining informed consent from leaders on whether they wish to partake in this study thus offering the right to withdraw in accordance with the APA Code of Ethics section A.3.3(a)-(j) and A.3.3(E) along with a disclosure to the nature and aims of this study. This was done as it was important that their busy schedules do not get disturbed as a result of the study being representing a good use of ethical practice.  Further ethical considerations included not keeping the records for longer than necessary and keeping biographical details confidential in secure secondary storage medium.

    SAMPLING

    For this investigation I decided to use opportunity sampling whereby I approach known individuals from the target population of leaders who are freely available at the time to partake in the study. The sampling process started with approaching known leaders from school management, parental workplaces and social circles who were then asked to forward the research materials to other leaders through worth-of-mouth to gain a more unknown and variable sample that could represent a diverse pool of leaders. Overall, the sample size came to a total of 55 comprising of a biased amount of 16 females and 38 males across multiple roles like management, directorship, professorship etc. As race, religion, race and other demographical factors were not of interest they were not considered in the sample but efforts were made to approach demographically diverse people to ensure a generalisable sample. The following data visualisations summarise the nature of the sample.

    Figure 2(a): Pie chart illustrating gender distribution of sample. 2(b) Pie chart illustrating leadership role

    PREDICTION

    It is hypothesised that a good majority of leaders in this sample will share adequate and similar levels of O, C and N traits while E and A traits may tend to differ from one leader to another. This prediction was vaticinated through my personal schema of an ideal leader who I envision to be open to change (Openness), hardworking (Conscientiousness) and stable in stressful situations (Neuroticism) meaning they should share similar scores in each of the traits. However, a leader’s extraversion may vary as some leaders may find social settings unenergetic to their sense of well-being despite having competent social skills. On similar lines, agreeableness could also vary as some leaders may appear pleasant around team mates while other maybe unempathetic and rigorous. This prediction is based entirely on personal opinions despite the fact that real-world scenarios maybe a lot different as there are no perfectly ideal leaders however it can be said that a perfect leader would encompass each of the BIG 5 traits in adequate levels according to his/her work ethic.

    RESULTS AND FINDINGS

    To ensure a sense of systematism in delivering and reporting the results of this study each trait has been analysed individually using three data visualisations followed by statistical deductions. Since this study assesses the similarity or dissimilarity within a set of scores, histograms and scatter diagrams are used to communicate the variability and spread of the scores alongside a bar graph that summarises a few statistical metrics that serve as dispersion measures. These metrics include the range, standard deviation (SD) and coefficient of variance (CV). The range assess the difference between the maximum and minimum values of a data set and gives a very brief idea of the spread of scores while SD and CV give a more comprehensive outlook on dispersion by assessing how far values are centred around the mean which then determine the consistency of scores.

    AGREABLENESS

    Through the results of this study, agreeableness shared the most similarity and consistency among the leaders of our sample. As visualised through both the shape of the score distribution on the histogram and scatter of scores against Participant ID on the scattergram, most A scores fall into the latter high end of the spectrum in a manner that is consistent and centred. The consistency and lack of variability in the scores is also justified through the use of statistical metrics with a scores ranging over 54 data points and being at least 11.88 data points away from its mean of 72.9 while the coefficient of variance is at 16% meaning that each result is moderately 84% closer to the each other and centred around the mean. All these metrics are comparatively lower to other traits concluding that willing to place others needs above yours, being pleasant and empathetic are attributes shared strongly amongst most of the leaders in our sample.

      OPENNESS

    Figure 4(a) Histogram of scores. 4(b)Scattergram of scores. 4(c) Bar chart summarising measures of dispersion for each trait.

    Openness was the second trait that shared the most similarity and consistency among the leaders of our sample. As visualised through both the shape of the score distribution on the histogram and scatter of scores against Participant ID on the scattergram, most O scores fall into the higher end of the spectrum in a manner that is consistent and centred. The consistency and lack of variability in the scores is also justified through the use of statistical metrics with a scores ranging over 52 data points and being at least 13.42 data points away from its mean of 72 while the coefficient of variance is at 18% meaning that each result is 82% closely dispersed around the mean. Overall, these metrics are lower than other traits but higher than the metrics deduced for Agreeableness. The visualisation together with its statistical evidence conclude that being open to change and allowing for diverse and unpredictable lifestyle is a critical dimension within leader as it is a strongly common trait amongst most of the leaders in our sample.

    CONSCIENTIOUSNESS

    Conscientiousness was a trait that was shared in a moderately similar pattern by our leaders in an almost split situation between the scores. As visualised through both the shape of the score distribution on the histogram and scatter of scores against Participant ID on the scattergram, most C scores fall into the median to higher ends of the spectrum in a manner that is comparatively more dispersed and scattered across a range of scores. The comparatively higher variability in the scores is also justified through the use of statistical metrics with a scores ranging over 65 data points and being at least 16.35 data points away from its mean of 69.1 while the coefficient of variance is at 24% meaning that each result is on average centred around the mean at 76%. Overall, these metrics are lower than other traits but higher than the metrics deduced for both Agreeableness and Openness suggesting greater inconsistency and variability. The visualisation together with the measures of dispersion calculated conclude that the propensity to be diligent, hard-working and inquisitive is a trait shared in a split manner amongst most of the leaders in our sample meaning that while some results are similarly high others moderately low.

    EXTRAVERSION

    Extraversion and neuroticism were the two traits that were shared in a strongly dissimilar pattern by our leaders but also in a split situation with most leaders falling towards the extraversion scale as opposed to the introversion scale due to the mean of 58.1. As visualised through both the shape of the score distribution on the histogram and scatter of scores against Participant ID on the scattergram, most E scores range from the lower to higher ends of the spectrum in a manner that is very dispersed and scattered across a range of scores. The high variability in the scores is also justified through the use of statistical metrics with a scores ranging over 69 data points and being at least 19.15 data points away from its mean of 58.1 while the coefficient of variance is at 33% meaning that only 67% of the results are centred and located around the mean. Overall, these metrics are way higher than C, O and A traits suggesting greater inconsistency and variability. The visualisation together with the measures of dispersion calculated conclude that the whether a leader is energised in social circles is something that varies form personality to personality and disapproves the statement that all leader must be extroverted personalities as most leaders in a sample scored moderately on extraversion.

    NEUROTICISM

    The trait was shared in a most dissimilar and inconsistent manner by the leaders f our sample was neuroticism. As visualised through both the shape of the score distribution on the histogram and scatter of scores against Participant ID on the scattergram, most N scores fall into the extremely low to higher ends of the spectrum in a manner that is extremely dispersed and scattered across a range of scores. The comparatively higher variability in the scores is also justified through the use of statistical metrics with a scores ranging over 86 data points and being at least 17.82 data points away from its mean of 46.2 while the coefficient of variance is at 39% meaning that only 62% of the scores are vaguely dispersed around the mean. Overall, these metrics were the lowest records through this investigation suggesting the greater inconsistency and variability in neuroticism among leaders. The visualisation together with the measures of dispersion calculated conclude that being stable and withstanding to be environment stress is a quality that varies form leader to leader meaning some leaders maybe calm and composed in stressful situations while others maybe unstable and pressurised.

    EVALUATION

    This evaluation is focused on examining the strengths and weaknesses of the research design I used in terms of five scientific aspects: generalisability, reliability, application, validity and ethicality.

    GENERALISABILITY

    In terms of generalisability, this study is strong as it considers a sample of 55 participants across several reputed organisations and leadership roles as well as few different age groups. This indicates that the results can be easily applied to the target population of leaders due to the sample being both valid and reasonably reliable to generalise. However, where it falls short is on gender where largely more males (22 more) have been considered over females which means that the results of the study represent mostly male leadership traits and cannot be fully generalisable to female populations. This reduced the generalisability of the study.

    RELIABILITY

    The Five-Factor Model, which is more commonly known as the Big Five, is a personality platform most commonly used for psychology studies and is widely considered the most scientifically reliable (Agostino, 2012) meaning the results reported would have been reliable to deduce conclusions from. Furthermore, all participants received the same treatment which extends to the sent message, questionnaire and BIG 5 test meaning the investigation was scientifically fair. However, there is still the possibility that the Big 5 tests results of each leader could alter when redone and this can threaten the study’s reliability alongside the fact that there would have been several environmental factors when the leaders did the tests at their own pace which could lead to a different result when replicated in a controlled setting.

    APPLICATION

    This study does have some applicative richness as it tells us the importance of openness and agreeableness to a leader indicating that those attempting to take up leadership must ensure that they are open-minded and willing to change while also being empathetic towards other and willing to place their team members needs above theirs. Application also extends to the fact that extraversion appears to be largely spread according to the statistical metrics meaning that it does not seem to interfere with one’s ability to stand as a leader which can reduce stigma or stereotypes caused by people foreseeing introverted personalities as less suitable for leadership.

    VALIDITY

    The study is valid in the sense that it used the well-known BIG 5 test measuring the exact traits it intends to measure rather than using a made-up test.A further strength lies in data generated through this investigation which were quantitative scores meaning the conclusion and findings deduced could easily be statistically proven and would have been less affected by the researcher bias.  However as seldom to questionnaires and survey, there is the tendency that the leaders would have show cased demand characteristics by showcasing the characteristics that leader should show or by conforming to the social desirability bias. There could have also been the impact of order effects which would have led the leaders to become fatigued towards the latter part of the tests leading to false responses. Furthermore, current issues at workplaces or familial stress could have also interfered when giving honest answers among the leaders of this sample. Overall, validity maybe poor but given the assumption that all participants were honest and integral in the study, it may have been less affected.

    ETHICALITY

    The study maintains good ethical practice as far as an online survey can go by giving the right to withdraw and informed consent which ensures that busy leaders are not disturbed from their commitments and rigorous schedules. However, a lot of sensitive information such as age, gender and name were gathered in this investigation which could have distressed our leaders’ privacy concerns.

    CONCLUSION

    This study clearly concludes that agreeableness and openness are the most shared leadership qualities at high levels in the spectrum while conscientiousness, extraversion and neuroticism are the least shared traits among leaders according to both visualisations and statistical metrics. This indicates that being willing to change and place others’ needs above are attributes that are shared similarly among leader while also being critical to leadership personalities.

    While being diligent, extraverted and stable in stress are qualities that vary amongst leadership personalities, it must be remembered that ideal leaders incorporate a perfect mix of the five traits.

    FURTHER RESEARCH OPTIONS

    This study can be further enhanced by incorporating new research ideas and questions that could be studies to break down the topic of leadership traits. A few question that can be assessed in further qualitative studies and research investigation include:

    • How could leadership traits differ between male and female personalities?
    • Which BIG 5 traits are ideal for leaders?
    • What traits do leaders showcase in stressful situations?
    • How does extraversion affect leadership?
    • Are leaders more open to change in real-life?

    REFERENCES

    Costa Jr, P.T. and McCrae, R.R., 1992. Four ways five factors are basic. Personality and individual differences, 13(6), (pp.653-665).

    Costa Jr, P.T. and McCrae, R.R., 1992. Four ways five factors are basic. Personality and individual differences, 13(6),( pp.653-665).

    Eaves, L., & Eysenck, H. (1975). The nature of extraversion: A genetical analysis. Journal of Personality and Social Psychology, 32(1), 102–112

    Gibb, C.A., 1947. The principles and traits of leadership. The Journal of Abnormal and Social Psychology, 42(3), p.267.

    Graziano, W. G., & Tobin, R. M. (2009). Agreeableness. In M. R. Leary & R. H. Hoyle (Eds.), Handbook of individual differences in social behavior (pp. 46–61). The Guilford Press.

    Kirkpatick, S.A. and Locke, E.A., 1991. Leadership: do traits matter? Academy of management perspectives, 5(2), pp.48-60.

    Matthews, G., Deary, I.J. and Whiteman, M.C., 2003. Personality traits (pp.03-05) Cambridge University Press.

    Pervin, L.A., 1994. A critical analysis of current trait theory. Psychological Inquiry, 5(2), (pp.103-113).

    Widiger, T. A. (2009). Neuroticism. In M. R. Leary & R. H. Hoyle (Eds.), Handbook of individual differences in social behavior (pp. 129–146). The Guilford Press.

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