Incorporating Exponentially Escalating Externalities Into Economics

Out of high school I intended to pursue an undergraduate business administration degree to help me become an entrepreneur. However, my multidimensional academic interests didn’t neatly fit into that single discipline. The cultures, values, and status quo of the world around me has long been one that I’ve tried to better understand. A deeply rooted affinity toward Western history directed me to study how the world’s dominant global political ideology, Democratic market capitalism, ascended globally. I studied political economy to help me understand my station in life as a poor immigrant who yearned to attain his own American Dream. I wondered why hadn’t Nicaragua also become part of the well-off industrialized world that US-born millennials inherited?[1] I answered this question and much more by focusing on how political, economic, and social development theory explained the history of any Latin American country’s unattained potential.

When deciding upon a major, I made it a goal to study abroad in Latin America to return to the place that had defined so much of me. My study aboard experience in Costa Rica allowed me to learn about a global United Nations metric called the world happiness index[2]. Costa Rica regularly scores higher than the US does on this scale. This fascinating multifaceted metric uses several data sources to develop a single value that reports how well the needs of a country’s population are being met. The intellectual endeavor that I would focus upon during my graduate studies is similar to a macroeconomic quantitative representation of happiness but its purpose is more economic like the Gini coefficient[3]. The Gini coefficient reflects economic inequality within a population. I would like to develop a value or set of values that reflect the long-term sustainability of an economic sector as a whole and for the individual firms that comprise that sector. These measures would be a more robust enumeration of the triple bottom line[4] framework.

The triple bottom line is a framework that recommends that companies commit to focusing on social and environmental concerns just as they do on financial profits. By harnessing databases from different private and public sources I aim to create a standardized measurement of the environmental[5] and social consequences[6] of a company’s operations and that of its respective industry at large. How would I create this standardized industry-specific approach? Existing databases of government consumer surveys, new measurements derived from existing government-mandated reporting of industry and firm-level business operations, and an in-depth understanding of an industry’s private databases. Which private databases are specifically of interest? Any which helps assess and regularly quantify its human, technological, financial, and capital investments. Why and how did I conclude that a change in my career trajectory merited a new direction?

After undergrad, a deep passion for technology and its career opportunities put me on a path to eventually become a technology market researcher for most of my twenties. My professional life started as the internet became more incorporated into most major corporation’s technology and overall strategy[7]^,[8]. Now the likes of relational databases like Salesforce have become inextricably entrenched into entire sectors of the US and global economy[9]. This trend will only continue as the companies which use this technology will have a substantial advantage. My professional interest in practicing quantitative marketing sciences was very much outside of the budgets of most mission-driven organizations. Thus, as a tech enthused data-driven millennial, I naturally gravitated toward researching emerging online behaviors at my first full-time research position at TNS Custom Research. Nonetheless, over the course of my professional research services career, I still yearned for the fulfillment provided by a mission-driven organization. This interest in giving back is one that was instilled in me from a very young age as a poor immigrant of divorced parents who was helped by the community, teachers, and family elders who always expected more from and for me.

Growing up poor let me live the basic laws of economics every day of my youth: supply and demand. Before I was aware of economics as an academic discipline, it was an elementary school-aged economic thinker who was feeling the purchase price parity (PPP) of my allowance[10] while buying my favorite candy at the local liquor store vs the grocery store. The experience of an economically disadvantaged upbringing gifted me the Dickensian understanding of it was to want for more in an Orange County with an abundant supply of what was well out of the reach of my pittance. Thus, even before my research career verified it, I now recognize that it was the empiricist who chose a quantitative and heavily theoretical behavioral sciences major instead of an undergraduate business degree. And it was at TNS Custom Research that I absolutely confirmed my passion for quantitative market research. Afterward a focus on consumer and business to business technology market research at CBS Interactive further developed a strong aptitude to uncover market opportunities that address business challenges across industries.

Years of research experience honed analytical expertise which relished using a variety of quantitative software tools and research methods to deliver informed decision making. Throughout my career, I gravitated toward and increasingly enjoyed dissecting research problems that employ different intellectual disciplines, methodologies, and require collaboration across multiple corporate functions. I’ve enjoyed utilizing my hard and soft research skills and have been fascinated by how disparate geographies, countries, and industries require different technologies, data sources, and types of measurement. In particular, my research of the development, marketing, and penetration of technology and data infrastructure has cultivated an appreciation for the insight that is possible through what is most commonly referred to as big data. As a business technology analyst, the information-led evolution I’ve witnessed within information-intensive industries like research insights, software, and computer hardware has been a precursor to the information revolution[11] that has already begun throughout other industries.

Now, my decision to pursue a multidisciplinary Ph.D. is driven by the same intellectual interest in the forthcoming political and economic importance of the online Latin American market in the United States[12] and the need to regulate consumer’s private online profile data[13]. I couldn’t forget that even classical economist Adam Smith argued for institutions to regulate market democracies[14] before the Keynesian school heralded a more interventionist government role in the economy[15]. Much of my undergraduate education emphasized the necessity to regulate market economies[16] in order to achieve optimal outcomes that benefit the greatest swath of society. Central to effective market regulation is the information required to enable informed decision making via government agencies[17] as they develop the legislation necessary to govern during a national crisis or to regulate established and emerging economic sectors.

The personal transportation industry is an example of a critical US economic sector that is already experiencing significant information lead transformation. Some of America’s oldest industrial giants, automakers, are now in an existential competition with many kinds of new transportation/logistics competitors to develop next-generation solutions that get people and products from point a to b as efficiently as possible. New forms of personal transportation solutions like on-demand electronic scooters, motorized publicly shared bicycles, mobile ridesharing applications, and self-driving vehicles depend on volumes of consumer and machine-generated data[18]. The revolution occurring in personal transportation is just one readily available wide-reaching example of how the technological ascendance of private and public multinational corporations has endowed them with the data analysis resources that governments have yet to utilize in their creation of legislation.

The Coronavirus pandemic is the most evident current example of the Federal government’s slow, limited, uncoordinated, and blunt monetary policy response[19]. But this is just another instance of a trend of our Federal government becoming increasingly caught off guard when they need to respond quickly, differently, effectively, and precisely at the national level. Previous examples include a long-overdue response to climate change[20], the increasing commute times in major US metropolitan areas[21], increasingly unaffordable housing markets in major US metropolitan areas[22], renewable energy adoption that is second to China[23], and insufficient wage growth in the face of years of low inflation rates and low unemployment rates since recovering from the Great Recession[24]. These problems are not new, they are not simple, they are interrelated, and require a more detailed understanding of how each of them contributes to one another financially, geographically, commercially, socially, and environmentally in order to better discern how to more precisely determine a proper political and economic national and international solution.

Many new information technology-driven industries have predominately emerged out of the US[25]. Meanwhile, the US government has not been able to respond quickly enough[26] to develop the legislation or regulatory framework for these kinds of companies to ensure the best economic outcomes for the greater public interest[27]. As an example, the majority of unintended victims of the success of globalization, automation, and 1099 dependent business models are the displaced labor forces of companies like General Motors[28]^,[29]. Concurrently the rampant prosperity of these next-generation information-centric sectors is geographically redistributing new economic opportunity and job security[30] unevenly away from the working-class communities who have suffered the most economic decline[31]. The new 1099 jobs[32] that are being created within the ‘gig economy’[33] have critical sub-optimal features inherent to the new business models upon which some of these information technology-enabled on-demand service companies heavily rely[34].

This circumstance could undermine the US consumer-service driven economy’s ability to avoid or respond to a strong and rapid downturn when a larger proportion of average household income growth and new jobs are related to discretionary on-demand spending[35]. Even in this specific example, a lot is unknown about the more granular linkages that might identify specific consumer micro-segments, sub-industries, or their respective multidimensional relationships. Once these multifaceted linkages are better understood, the potential to more specifically harness them and their respective multiplier effects[36] could magnify the impact of an economically virtuous cycle and potentially require less initial government intervention when it is first applied as a smaller preventative deterrent against the possibility of larger upcoming macroeconomic headwinds. The current approach of identifying a recession after two-quarters of economic fallout is no longer an appropriate response to the interconnected nature of our international banking, finance, and trade economies. Within the time it takes to identify the problem at hand it has turned into a high magnitude all-involving crisis[37]. The tools we had then didn’t mitigate the underlying economic morass and eventually required the development of new gargantuan and black box government intervention: quantitative easing[38]. The justification then emerged that the biggest organizations that caused the Great Recession are “too big to fail”[39]. The too big to fail justification in capitalist America clearly establishes a rationale to ensure that large organizations are never imperiled from an all-involving systemic risk by mitigating it from the onset of any more minor systematic risk.

Thus, if governments could tap into the information and technological infrastructure private corporations use to manage their own financial investments, coordinate transnational operations and develop human, natural and capital resources across the globe then its Federal government could better manage to avoid the kind of circumstances that lead to the Great Recession[40] or the upcoming 2020 recession that we may have already entered[41]. My graduate studies would focus on enhancing the capability to responsibly access private information systems to enforce and develop the legal, financial, economic, and ethical frameworks that will advance the long-term prosperity and stability of our world’s interdependent environment, international economy, global financial markets, and thus geopolitical stability. It is my hope that this framework would help to provide the metrics to combat some of the decades-long ills that have unnecessarily plagued the US: climate change, homelessness, income inequality, rising commute times, and unaffordable cost of living expenses. Without a more data-integrated approach to corporate governance, the institutions that are expected to steward the world’s leading economies will continue to fail to keep up with the pace of how our economies develop our most innovative information industries. If the US does not maintain its global leadership within these emerging industries as they develop it will further erode US geopolitical leadership[42].

How would I ensure that companies want to take part in this very data sensitive undertaking? Give any participating company an undeniable and serious advantage to getting the Federal assistance the next time a participating company needs the US government to act to prevent or respond to the next recession. The problems our nation faces, like income inequality and climate change, are not specific to the US or its economy and their prevalence imperils the US economy. Their causes are international and interdependent and as are these problem’s respective solutions. These problems have only deepened over the last few decades and our current systems can’t quickly or accurately measure their shifts or growth. As automation and digital business management systems become more prevalent throughout key economic sectors the most impactful and useful data-based governance systems will increasingly become feasible.

For example, a more sensitive digital measurement of natural resource utilization and economic output could help track from cradle to grave how industries could improve their production processes and delivery cycles to be more environmentally friendly. Analyzing data from digital management systems of large-scale industries could be one of the best applications of a regulation-focused blockchain system[43] that captures, analyzes, and synchronizes how any product is sourced, made, delivered and sold to its final consumer. Industries are already adopting computerized automation and thus are producing the digital data streams that could enable more efficient and up-to-date economic governance systems. Examples of these include consumer services, natural resource extraction and development, intermediate product manufacturing, final product assembly, international product logistics, and self-serve retail consumer sales.

A multidisciplinary Ph.D. will allow me the opportunity to focus on developing a feasible framework for an industry that is primed to mitigate its environmental impact and or ensure efficient long-term resource utilization by undergoing better measurement of the input, output, and impact of its production and distribution processes. This new data science framework could be thought of as the business operations informatics application which harnesses a triple bottom line accounting framework. This new framework could provide corporations with the data-backed profit-motivated rationale to make the changes to their operations that would address the negative externalities of their business by more directly connecting the longer-term social, environmental, and economic consequences of their activities to a company’s financial bottom line. After developing this framework, its adoption might be best accelerated by offering the funding to enable existing companies to make the financial investment into changes to become more ethical employers, environmentally sustainable actors, and socially responsible organizations. An existing investment firm or the establishment of a new kind of socially motivated venture capital or equity investment firm that is focused on promoting the implementation of this framework could help address major problems like climate change or economic inequality.

[1] As determined by the GDP per capita comparison of Latin American countries: https://data.worldbank.org/indicator/

[2] https://en.wikipedia.org/wiki/World_Happiness_Report#Metrics

[3] https://en.wikipedia.org/wiki/Gini_coefficient

[4] https://en.wikipedia.org/wiki/Triple_bottom_line

[5] https://www.nbs.net/articles/systematic-review-measuring-valuing-environmental-impacts

[6] https://www.nbs.net/articles/the-main-report-measuring-and-valuing-social-capital

[7] https://www.businesswire.com/news/home/20200311005553/en/Enterprise-Resource-Planning-ERP-Software-Market-2020-2024

[8] https://www.seattletimes.com/business/technology/how-microsoft-emerged-from-darkness-to-embrace-the-cloud/

[9] https://hostingtribunal.com/blog/cloud-adoption-statistics/#gref

[10] https://en.wikipedia.org/wiki/Purchasing_power_parity

[11] https://hbr.org/2012/10/big-data-the-management-revolution

[12] https://multimarketresearcher.com/2009/04/20/the-future-of-social-media/, https://multimarketresearcher.com/2009/02/22/the-markets-recognition-of-hispanics-online/