New research reveals that companies often “opinion shop” to shape their financial reality. Photo via rice.edu

Firms often have to estimate the “fair value” of their investments, meaning they have to declare what an asset is worth on the market. To avoid the potential for bias and manipulation, companies will use third-party services to provide an objective estimate of their assets’ fair value.

But nothing prevents a company from seeking multiple third-party estimates and choosing whichever one suits their purpose.

In a recent study, Shiva Sivaramakrishnan (Rice Business) and co-authors Minjae Koo (The Chinese University of Hong Kong) and Yuping Zhao (University of Houston) examine two motives for switching third-party evaluators: “opinion shopping” and “objective valuation.”

Firms that opinion shop are looking for a third-party source to make their investments look better on paper. For example, if Service A says an asset is worth $80 — and that means the company would have to take an accounting loss — the company might switch to Service B, which says the asset is worth $90. By using the higher estimate from Service B, the company avoids a loss.

Opinion shopping can be a dangerous practice, both on a macro level and for the specific firms that engage in it. Not only does it reduce the quality of fair value estimates for everyone, it means some company assets are potentially overvalued. And if those assets ever decline in value for real, the company will eventually take a loss.

Moreover, opinion shopping opens the door to managerial opportunism. If assets are valued more highly, managers are likely to receive credit and potentially use that perceived accomplishment to advance their careers.

There are reasons for companies to go the other way. In the hypothetical scenario above, our company might switch from Service B ($90) to Service A ($80) to receive a more accurate and objective estimate. The “objective valuation” motive helps companies meet regulatory requirements and ensure estimates reflect true market value. What’s more, the objective valuation motive helps curb managerial buccaneering.

The study looks at when and why life insurance companies will switch their third-party review service. The team finds that both motives — opinion shopping and objective valuation — are common. Sometimes companies want to better align their fair value estimates with what similar assets are trading for in the market. Other times, they want assets to look better on paper.

Of the two motives, opinion shopping is the more dominant, particularly when they are in conflict with each other. On the whole, evidence suggests that companies switch price sources strategically to inflate estimates and avoid losses, rather than to get more accurate estimates.

The study has implications for investors, regulators and researchers. “Opinion shopping” could be prevalent in non-financial industries, as well — especially public firms with capital market incentives. More disclosure around price sources could improve estimate reliability.

Future research could examine asset valuation practices and motives in other sectors such as banking, real estate and equity investments. Are some industries more prone to opinion shopping than others? What factors make opinion shopping or objective valuation more likely? Are there certain signals or patterns that indicate when a company is opinion shopping versus seeking objectivity?

Answers to these questions could help discern acceptable from unacceptable third-party source switching. And understanding if certain types of companies are more at risk could help regulators and auditors focus their efforts.

The bottom line:

Accurate accounting matters. While external sources are better for measuring the fair value of any given asset, companies can distort the very concept of fair value estimates by changing their source. More rigor, transparency and auditing around price sources could curb manipulation and improve estimate reliability.

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This article originally ran on Rice Business Wisdom and was based on research from Shiva Sivaramakrishnan, the Henry Gardiner Symonds Professor of Accounting at Rice Business.

Allowing employees to select their incentives increases both the quantity and quality of their ideas. Photo via Getty Images

Rice research: Incentives increase employee contribution to company success

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Companies can increase not only the volume but also the quality of employee suggestions and ideas by offering rewards and a choice, according to a study we published in 2022.

We conducted the study on 345 telemarketers at a call center in Taiwan, which already had a suggestion program set up to solicit creative ideas to improve the organization. The company rewarded those who suggested ideas deemed the most valuable by giving them a trophy.

We wanted to see how tweaking the reward changed the quantity and quality of suggestions. So we invited the employees to submit ideas and that if their suggestions ranked among the top 20% most creative ideas – as evaluated by a team of managers and researchers – they would receive one of four rewards: US$80 in cash for themselves, $80 to share with colleagues, $80 to give to a preferred charitable organization or priority when selecting days off. About half of the employees were offered a choice of the four rewards they would receive for submitting ideas. We then randomly assigned one of the four rewards to the remaining employees.

In total, we received and evaluated 144 ideas over a one-month period.

We found that employees who were given a choice of reward submitted 86% more ideas than those who were told what they would be getting. Moreover, the average creativity score of their ideas was 82% higher. Overall, our suggestion program elicited double the number of ideas as the company’s own program and resulted in ideas that were ranked 84% more creative.

Why it matters

Soliciting employee ideas can be a key driver of innovation in organizations.

When employees share their ideas about products, services or policies using a suggestion program, an organization can take those ideas and refine and then implement them.

These implemented ideas can enhance an organization’s ability to adapt and compete. A 2003 study of 47 organizations found that ideas submitted to employee suggestion programs saved those organizations more than $624 million in a single year.

Our own study suggests small incentives could have a significant impact on the quantity and quality of those employee suggestions.

What’s next?

Research is still needed on whether there is an optimal number of rewards that organizations should offer to get more submissions. One past study found that when employees were asked to choose from a large set of rewards, they felt overwhelmed and produced few ideas.

Future research can also test whether our results can be found in other types of organizations, with employees in other types of jobs and in other parts of the world. We plan to examine these issues in our future studies of suggestion programs.

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This article originally ran on Rice Business Wisdom and was based on research from Jing Zhou, the Mary Gibbs Jones Professor of Management and Psychology in Organizational Behavior at the Jones Graduate School of Business of Rice University.

Here's what you should learn from social media influencers for your own business marketing. Photo via Getty Images

Key business marketing tips to take from top social media creators, according to these Houston researchers

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Influencer marketing is booming, with companies allocating 10 to 25 percent of their advertising budgets to influencer-led strategies. Between 2016 and 2020, the number of sponsored posts rose from 1.26 million to 6.12 million, and overall spending in the past few years has grown by billions.

When partnering with online ambassadors, brands certainly want a large influencer audience. However, audience size does not necessarily reflect the amount influencers are paid. Influencers with similar-sized audiences can be paid very different amounts.

That’s partly because brands also want an engaged influencer audience. An influencer may have many followers, but if those followers don’t actively interact with content, the influencer’s reach is limited. Engagement metrics like comments, shares and “likes” are often a more reliable indicator of impact than follower count alone.

The problem brands face — no matter who the influencer is — is that sponsored posts typically see a plunge in engagement, making it difficult to measure their success. Very little research examines this effect and how influencers can mitigate it.

In a new study, Rice Business professors Jae Chung and Ajay Kalra take up this issue, along with Stanford professor Yu Ding. According to the researchers, one way of boosting engagement overall, even on sponsored content where engagement often falls, is for influencers to increase audience perceptions of authenticity, perceived similarity, and interpersonal curiosity.

Even in a world full of filters and careful staging, authenticity is a key differentiator for leaders, businesses and personalities. One powerful way of appearing true to one’s own personality or character is to effectively share life stories. But social media influencers walk a fine line between presenting their authentic selves and monetizing their platforms.

To attract followers and content sponsors, influencers must curate the images they share, the words they say, and the timing and cadence of their posts. It’s a delicate dance between providing value through a genuine audience connection and aligning with brand interests.

Here are three simple but powerful ways that influencers can boost engagement by highlighting close relationships:

  • Post photos that include one or two close friends or family members.
  • Mention friends and family in the caption.
  • Use first-person language (e.g., “I,” “my” and “we”).

Referencing close social ties is an especially powerful way to boost engagement. According to Professor Chung, “Intimate social ties can make influencers seem more authentic and sponsored messaging seem less transactional.” This effect holds true even when controlling for variables like gender, frequency of posting, use of emojis and hashtags, and audience familiarity with the influencer.

The team analyzed over 55,000 Instagram posts from 763 top influencers during the second half of 2019. One of their most distinctive findings is that, in terms of boosting audience engagement, the ideal number of faces in a photo is three — the influencer plus two friends or family members. For an Instagram audience, this numerical face count proves a surprisingly effective metric for assessing the closeness of relationships.

Influencers can also seem more genuine to followers by referencing intimate social ties in their captions. Terms like “grandpa,” “bestie” and “soulmate” give followers access to an inner circle usually reserved for loved ones, making them feel more connected and invested in the influencer’s world and worldview.

In one experiment, study participants were shown a series of Instagram posts supposedly written by actor Jessica Alba. Testing the impact of language on the perception of close ties, the researchers wrote three different captions for the same image. One caption mentions Alba’s daughter (“Styling by my daughter. Isn’t this outfit cute?”). Another references a distant tie (“Styling by designer Kelmen. Isn’t this outfit cute?”). A third post provided a baseline by indicating no ties at all.

Study participants were asked to select which posts they liked most. The results supported the research hypothesis. Posts mentioning close relationships are significantly more likable than posts mentioning distant ties or no ties.

The team also examined the impact of expressing emotion on Instagram. Does sharing feelings — either positive or negative — help or hurt audience engagement? Using the Linguistic Inquiry and Word Count (LIWC) language processing program, the researchers categorized and analyzed the strength and valence of emotion-related words and emojis (e.g., “love,” “nice,” “frustrated,” “sad”).

What they found is surprising. Expressing emotion boosts audience engagement, perhaps because it bridges a perceived gap of celebrity between influencer and audience. But what’s interesting is that negative emotions are more powerful than positive ones. According to the researchers’ dataset, negative emotions are expressed only 9.08 percent of the time, while positive feelings are shared 36.03 percent of the time. So, one way of interpreting the finding is that the comparative rarity of negative feeling could take some readers by surprise, and thereby incite a stronger sense of authenticity.

Importantly, all of these findings regarding audience engagement most likely apply to platforms where a gray line exists between private and public life.

And, on this note, the researchers warn against the potential for oversharing and exploiting family and friends for the sake of monetizing content.

But the study shows how brands can strategically sponsor posts that incorporate close ties in photos, express emotion, or share anecdotes in first-person language.

By quantifying tactics to achieve a greater perception of authenticity, the research provides valuable guidance on how to cut through the noise on social media. One of the paths to a more engaged audience, it turns out, runs through an influencer’s inner circle.

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This article originally ran on Rice Business Wisdom and was based on research from Jaeyeon (Jae) Chung, an assistant professor of marketing at Rice Business, Yu Ding an assistant professor of marketing at Stanford Graduate School of Business, and Ajay Kalra, the Herbert S. Autrey Professor of Marketing at Rice Business.

Serious product reviewers need peers and audiences to see them as credible. But new research indicates that pursuing credibility may compromise the objectivity of their evaluations. Photo via Getty Images

Houston research: How social pressures are affecting digital product evaluations

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Theoretically, product evaluations should be impartial and unbiased. However, this assumption overlooks a crucial truth about product evaluators: They are human beings who are concerned about maintaining credibility with their audience, especially their peer evaluators.

Because evaluators must also care about being perceived as legitimate yet skillful themselves, certain social pressures are at play that potentially influence their product reviews.

Research by Minjae Kim (Rice Business) and Daniel DellaPosta (Penn State) takes up the question of how evaluators navigate those pressures. They find that in some cases, evaluators uphold majority opinion to appear legitimate and authoritative. In other contexts, they offer a contrasting viewpoint so that they seem more refined and sophisticated.

Pretend a movie critic gives an uplifting review of a widely overlooked film. By departing from the aesthetic judgments of cinema aficionados, the reviewer risks losing credibility with their audience. Not only does the reviewer fail to understand this specific film, the audience might say; they fail to understand film and filmmaking, broadly.

But it’s also conceivable, in other situations, that the dissenting evaluator will come across as uniquely perceptive.

What makes the difference between these conflicting perceptions?

Partly, it depends on how niche or mainstream the product is. With large-audience products, Kim and DellaPosta hypothesize, evaluators are more willing to contradict widespread opinion. (Without a large audience, contradicting opinions are like the sound of a tree that falls in a forest without anyone nearby to hear.)

The perceived classiness of the product can affect the evaluator’s approach, as well. It’s easier to dissent from majority opinion on products deemed “lowbrow” than those deemed “highbrow.” Kim and DellaPosta suggest it’s more of a risk to downgrade a “highbrow” product that seems to require more sophisticated taste (e.g., classical music) and easier to downgrade a highly rated yet “lowbrow” product that seems easier to appreciate (e.g., a blockbuster movie).

Thus, the “safe spot” for disagreeing with established opinion is when a product has already been thoroughly and highly reviewed yet appears easier to understand. In that case, evaluators might sense an opportunity to stand out, rather than try to fit in. But disagreeing with something just for the sake of disagreeing can make people think you’re not a fair or reasonable evaluator. To avoid that perception, it might be better to agree with the high rating.

To test their hypotheses, Kim and DellaPosta used data from beer enthusiast site BeerAdvocate.com, an online platform where amateur evaluators review beers while also engaging with other users. Online reviewers publicly rate and describe their impressions of a variety of beers, from craft to mainstream.

The data set included 1.66 million user-submitted reviews of American-produced beers, including 82,077 unique beers, 4,302 brewers, 47,561 reviewers and 103 unique styles of beer. The reviews spanned from December 2000 to September 2015.

When the researchers compared scores given to the same beer over time, they confirmed their hypothesis about the conditions under which evaluators contradict the majority opinion. On average, reviewers were more inclined to contradict the majority opinions for a beer that had been highly rated and widely reviewed. When reviewers considered a particular brew to be a “lowbrow,” downgrading occurred to an even greater extent.

Kim and DellaPosta’s research has implications for both producers and consumers. Both groups should be aware of the social dynamics involved in product evaluation. The research suggests that reviews and ratings are as much about elevating the people who make them as they are about product quality.

Making evaluators identifiable and non-anonymous may help increase accountability for what they say online — a seemingly positive thing. But Kim and DellaPosta reveal a potential downside: Knowing who evaluators are, Kim says, “might warp the ratings in ways that depart from true objective quality.”

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This article originally ran on Rice Business Wisdom and was based on research from Minjae Kim, assistant professor of Management – Organizational Behavior at Rice Business, and Daniel DellaPosta, associate professor of Sociology and Social Data Analytics at Pennsylvania State University.

Researchers created a mathematical model that helps transplant centers make decisions about when to move forward with a matching donor and when to wait. This work can potentially help decision making in other industries. Photo via Getty Images

Houston researchers build life-saving decision making mathematical model with big potential

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To wait, or not to wait? That is the question — or at least it might be, if you need a kidney transplant.

Nearly 89,000 Americans with chronic kidney disease are on a waitlist for a new organ, and an estimated 13 people die each day while awaiting a transplant. But there are real costs to matching patients with the first donor that becomes available, just as there are equally real costs to having them wait in hopes of finding a better one.

Recently, Rice Business professor Süleyman Kerimov and colleagues at Stanford University and Northwestern University developed a mathematical model that helps clarify when it's best to match patients to donors as quickly as possible and when it's best to wait.

Their findings, which appear in two papers published in Management Science and Operations Research, respectively, could help optimize all manner of matching markets in which participants seek to connect with potential partners based on mutual compatibility — a sprawling category that encompasses everything from e-commerce platforms to labor markets that match employees with employers.

Kerimov and his colleagues focused on programs that match live kidney donors with people who need transplants. Live donors typically volunteer to give one of their kidneys to a loved one. But biological differences between a donor and their intended recipient can render the pair incompatible.

Kidney exchange programs solve this problem by swapping donors amongst different patient-donor pairs, choreographing a kind of kidney-transplant square dance aimed at finding a compatible partner for every willing donor.

In countries such as Canada and the Netherlands, kidney-matching programs perform a batch of matches every few months (called periodic policies). American programs, meanwhile, tend to perform daily matches (called greedy policies). Both models seek to produce the greatest number of high-quality transplants possible, but they each have advantages and disadvantages.

Less frequent matches in a periodic policy allow more patient-donor pairs to accumulate in the kidney exchange network, creating potential for better matches over time. But this approach risks making some patients sicker as they wait for a better match that might never appear.

Arranging feasible matches as soon as they become available in a greedy policy avoids that predicament. But it means passing up the opportunity to make a potentially better match that could represent the possibility of a longer, healthier life.

Balancing these trade-offs is tricky. There is no way of predicting precisely when a patient-donor pair with a particular set of characteristics will show up at the kidney-exchange network. And in the world of organ transplants, there are no do-overs.

Kerimov and his colleagues have constructed a mathematical model that represents a simplified version of a kidney exchange network.

Within the model, the researchers could dictate which patient-donor pairs could be matched with one another. They can also assign different values to individual matches based on the number of life years they provide. And they can establish the probability that various kinds of patient-donor pairs with particular characteristics might arrive at the network and queue up for a transplant at any given time.

Having set those parameters, the researchers applied different matching policies and compared the results. As it turns out, the answer to whether one should wait or not is: It depends.

To determine which policies generated the best outcomes — i.e., performing matches either daily or periodically — the researchers calculated the difference between the total value in life years that could possibly be generated within the network and the amount generated by a specific policy at a particular point in time. The goal was to keep that number, evocatively dubbed "all-time regret," as small as possible over both the short and long term.

In their first paper, Kerimov and his team explored a complex network in which donor kidneys could be swapped amongst three or more patient-donor pairs. When such multiway matches were possible, the cost of applying a daily-match policy turned out to be onerous. Using all available matches as quickly as possible eliminated the chance of later performing potentially higher-value matches.

Instead, the researchers found they could minimize regret by applying a periodic policy that required waiting for a certain number of patient-donor pairs to arrive before attempting to match them. The model even allowed the team to calculate precisely how long to wait between matchmaking sessions to get the best possible results.

In their second paper, however, the team looked at a simpler network in which kidneys could only be swapped between two donor-patient pairs. Here, their findings contradicted the first: Applying a daily-match policy minimized regret; a periodic matching process yielded no benefit whatsoever.

To their surprise, the researchers discovered they could design a foolproof algorithm for making two-way matches in simple networks. The algorithm employed a ranked list of possible match types; and the researchers found that no matter how many patient-donor pairs of various kinds randomly arrived at the network, the best choice was always simply to perform the highest-ranked match on the list.

In future research, Kerimov hopes to refine the model by feeding it data on real patient-donor pairs that have participated in actual kidney exchange programs. This would allow him to create a more realistic network, more accurately calculate the likelihood that particular kinds of patient-donor pairs will show up, and assign values to matches based not only on life years but also on rarity and difficulty. (Certain blood types and antibody profiles, for example, are rarer or more difficult to match than others.)

But Kerimov already suspects that in a real-world situation, the wisest course of action will be to alternate between periodic and greedy policies as circumstances dictate. In a simple region within a kidney exchange network that only allows for two-way matches, pursuing a greedy policy that involves taking the first match that appears on a fixed menu of options would be the best choice. In a more complex region that allows three-way matches, however, pursuing a periodic matching policy that involves waiting to make rarer and more difficult matches would ultimately offer more patients more years of healthy life.

The benefits of choosing flexibly between greedy and periodic policies should hold for any kind of matching market that can be represented by a network with simpler and more complex regions, such as a logistics system that matches online orders to delivery trucks or a carpooling system that matches passengers with drivers across different parts of a city.

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This article originally ran on Rice Business Wisdom and was based on research from Süleyman Kerimov, an assistant professor of management – operations management in the Jones Graduate School of Business at Rice University.

There's no crystal ball, but this researcher from Rice University is trying to see if some metrics work for economic forecasting. Photo via Getty Images

Houston researcher tries to crack the code on the Fed's data to determine economic outlook

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Research by Rice Business Professor K. Ramesh shows that the Fed appears to harvest qualitative information from the accounting disclosures that all public companies must file with the Securities and Exchange Commission.

These SEC filings are typically used by creditors, investors and others to make firm-level investing and financing decisions; and while they include business leaders’ sense of economic trends, they are never intended to guide macro-level policy decisions. But in a recent paper (“Externalities of Accounting Disclosures: Evidence from the Federal Reserve”), Ramesh and his colleagues provide persuasive evidence that the Fed nonetheless uses the qualitative information in SEC filings to help forecast the growth of macroeconomic variables like GDP and unemployment.

According to Ramesh, the study was made possible thanks to a decision the SEC made several years ago. The commission stores the reports submitted by public companies in an online database called EDGAR and records the IP address of any party that accesses them. More than a decade ago, the SEC began making partially anonymized forms of those IP addresses available to the public. But researchers eventually figured out how to deanonymize the addresses, which is precisely what Ramesh and his colleagues did in this study.

"We were able to reverse engineer and identify those IP addresses that belonged to Federal Reserve staff," Ramesh says.

The team ultimately assembled a data set containing more than 169,000 filings accessed by Fed staff between 2005 and 2015. They quickly realized that the Fed was interested only in filings submitted by a select group of industry leaders and financial institutions.

But if Ramesh and his colleagues now had a better idea of precisely which bellwether firms the Fed focused on, they still had no way of knowing exactly what Fed staffers had gleaned from the material they accessed. So the team decided to employ a measure called "tone" that captures the overall sentiment of a piece of text – whether positive, negative, or neutral.

Building on previous research that had identified a set of words with negatively toned financial reports, Ramesh and his colleagues examined the tone of all the SEC filings accessed by Fed staff between one meeting of the Federal Open Markets Committee (FOMC) and the next. The FOMC sets interest rates and guides monetary policy, and its meetings provide an opportunity for Fed officials to discuss growth forecasts and announce policy decisions.

The researchers then examined the Fed's growth forecasts to see if there was a relationship between the tone of the documents that Fed staff examined in the period between FOMC meetings and the forecasts they produced in advance of those meetings.

The team found close correlations between the tone of the reports accessed by the Fed and the agency’s forecasts of GDP, unemployment, housing starts and industrial production. The more negative the filings accessed prior to an FOMC meeting, for example, the gloomier the GDP forecast; the more positive the filings, the brighter the unemployment forecast.

Ramesh and his colleagues also compared the Fed's forecasts with those of the Society of Professional Forecasters (SPF), whose members span academia and industry. Intriguingly, the researchers found that while the errors in the SPF's forecasts could be attributed to the absence of the tonal information culled from the SEC filings, the errors in the Fed’s forecasts could not. This suggests both that the Fed was collecting qualitative information that the SPF was not—and that the agency was making remarkably efficient use of it.

"They weren’t leaving anything on the table," Ramesh says.

Having solved one mystery, Ramesh would like to focus on another; namely, how does the Fed identify bellwether firms in the first place?

Unfortunately, the SEC no longer makes IP address data publicly available, which means that Ramesh and his colleagues can no longer study which companies the Fed is most interested in. Nonetheless, Ramesh hopes to use the data they have already collected to build a model that can accurately predict which firms the Fed is most likely to follow. That would allow the team to continue studying the same companies that the Fed does, and, he says, “maybe come up with a way to track those firms in order to understand how the economy is going to move.”

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This article originally ran on Rice Business Wisdom and was based on research from K. Ramesh is Herbert S. Autrey Professor of Accounting at Jones Graduate School of Business at Rice University.

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Report: Houstonians need $12K more to live comfortably than they did last year

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As inflation and the cost of living rise in most places around the United States, so does the amount of money a resident needs to live comfortably. But Houstonians are faring far better than residents of some of the biggest cities in America.

Houston requires the lowest salary needed to live comfortably in 2024, according to a new SmartAsset report. Specifically, they say, Houston ranks No. 1 for "the lowest annual salary needed for a single adult to live in sustainable comfort using the 50/30/20 budgeting rule" — that is, 50 percent of a salary allocated toward needs (housing, groceries, transportation); 30 percent toward wants (entertainment and hobbies); and 20 percent toward paying off debt, saving, or investing.

Houstonians need to make $75,088 individually to lead a comfortable lifestyle and avoid living paycheck to paycheck, or a $36.10 hourly wage, says the report, which analyzed 99 major U.S. cities.

The necessary salary to live a financially stable life in Houston is nearly $12,000 more than in SmartAsset's 2023 report, which said Houston residents needed to make $62,260 a year to live comfortably in 2023.

New in the 2024 report, SmartAsset also found that for a Houston-based family of four (two adults with two children), the total combined income needed to live a secure lifestyle is currently $175,219.

Breaking down the cost of living in Houston SmartAsset gathered data from MIT’s Living Wage Calculator to determine the cost of living for a childless adult and for a family of four (two working adults and two children) in the 99 largest American cities.

To live a financially stable life in Houston based on the 50/30/20 strategy and using SmartAsset's salary requirement, a childless Houstonian would need to spend $37,544 of their salary on living expenses, about $22,526 for discretionary expenses, and put about $15,017 toward their savings or debt payments.

Meanwhile, families of four would have to spend about $87,610 on living expenses, $52,566 on entertainment or hobbies, and put away $35,044 into savings or paying down debt in order to live comfortably in Houston, based on the study's findings.

Despite residents' growing financial constraints, the income necessary to live in Houston is much better than the national average of $96,500 a year for singles and $235,000 per year for a family of four, SmartAsset says.

Elsewhere in Texas
Among Texas cities, Austin has the highest necessary income required to live a financially stable life, but the capital city ranked No. 65 out of all 99 cities in the report. A single adult living in Austin would need to make $47.96 an hour, or $99,757 a year, to live comfortably. The combined income needed for two adults with two children is $223,891.

Here's how other Texas cities stack up, from lowest salary to highest:

  • No. 2 – El Paso ($75,254 for single adults, $175,219 for families)
  • No. 3 – Lubbock ($75,379 for single adults, $181,043 for families)
  • No. 5 – Laredo ($78,458 for single adults, 179,046 for families)
  • No. 16 – Corpus Christi ($82,493 for single adults, $192,275 for families)
  • No. 25 – San Antonio ($85,072 for single adults, $200,762 for families)
  • No. 42 – [Tied] Dallas, Plano, Irving, Garland ($91,770 for single adults, $208,000 for families)
  • No. 57 – [Tied] Fort Worth, Arlington ($94,765 for single adults, $214,490 for families)

Not surprisingly, the U.S. city that requires the highest salary to live comfortably is New York City. Single adults would need to make an hourly wage of $66.62, or an annual salary of $138,570, to prevent living paycheck to paycheck. And for a family of four, the combined salary needed is $318,406 a year, SmartAsset says.

The full report and its methodology can be found on smartasset.com.

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This article originally ran on CultureMap.

UK, Texas pledge closer trade ties in recently signed agreement

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Britain signed a trade agreement with Texas on Wednesday, the eighth the U.K. has inked with a U.S. state in the absence of a wider free trade deal with the U.S. government.

Texas Gov. Greg Abbott signed the document in London alongside U.K. Trade Secretary Kemi Badenoch. Abbott also met with Prime Minister Rishi Sunak, who told him it was an “exciting moment.”

The "statement of mutual cooperation” is not a full trade deal because individual U.S. states do not have the power to sign those, but it commits Britain and Texas to improve cooperation between businesses and tackle regulatory barriers to trade.

“Understand that this is far more than a document,” Abbott said. “What we signed our names to today is a pathway to increased prosperity.”

During and after Britain’s 2016 referendum on European Union membership, supporters of Brexit argued that a chief benefit of leaving the bloc, and its vast free market of almost half a billion people, was the chance for the U.K. to make new trade deals around the world.

U.K.-U.S. trade talks were launched with fanfare soon after Britain left the EU in 2020, but negotiations faltered amid rising concern in the U.S. administration about the impact of Brexit, especially on Northern Ireland.

Instead, Britain has resorted to signing agreements with states including Florida, Indiana and North Carolina.

Although these agreements do not lower tariffs, as a free trade deal would, they can provide some help for businesses through recognizing U.K. qualifications or addressing state-level regulatory issues.

Overheard: Innovators sound off on future of work, converging industries at Houston House at SXSW 2024

Eavesdropping in Austin

Houston innovators talked big topics at SXSW 2024 — from the startup scaling and converging industries to the future of work.

Houston House, which was put on by the Greater Houston Partnership on March 11, hosted four panels full of experts from Houston. If you missed the day-long activation, here are some highlights from the experts who each commented on the future of the Bayou City when it comes to startups, technology, innovation, and the next generation's workforce.

"When we think about Houston, we think about access to at-scale infrastructure, amenities, and workforce and talent pools."

— Remington Tonar, co-founder and chief growth officer at Cart.com, says about why the company chose to return its headquarters back to Houston last year. One of these amenities, Tonar explained, is Houston's global airports.

"If New York and Austin had a baby, it would be Houston, because you have friendly people with a big-city culture."

— Mitra Miller, vice president and board member of Houston Angel Network, says, adding that Houston has a cost efficiency to it, which should be at the forefront of founders' minds when considering where to locate.

"We are not only attracting global talents, we are also attracting global wealth and foreign investments because we are the rising city of the future. We are the global launch pad where you can scale internationally very quickly."

— Sunny Zhang, founder of TrueLeap, says adding how there's a redistribution of global workforce happening when you consider ongoing global affairs.

"We overwhelmingly as a company, and my co-founder would agree, knew we had to go the Houston path. And we started funneling a lot more resources here."

— Carolyn Rodz, co-founder and CEO of Hello Alice, says, explaining that the pandemic helped equalize the talent across the country, and this has been to the benefit of cities like Houston.

"Houston is here with arms open, welcoming people and actively recruiting."

— Sean Kelly, co-founder and CEO of Amperon, says, emphasizing how Texas has made moves to being business friendly. Amperon was founded in New York, before moving to Houston a couple years ago.

"There is a revolution starting to happen in Houston right now."

— Trevor Best, co-founder and CEO of Syzygy Plasmonics, says, first commenting on the momentum from Rice University, where his company's technology originates from. But, as he adds, when you compare the ecosystem when the startup was founded in 2019 to where it's at now, "there is so much more happening."

"Houston has a critical mass in terms of aerospace."

— Stephanie Munez Murphy of Aegus Aerospace says, saying specifically that NASA's Johnson Space Center holds some responsibility for that. "JSC is the home of opening up space commercialization."

"There's diversity in industries people are coming from, but also in terms of experience and expertise that (Houstonians) have."

— Robyn Cardwell of Omniscience says, adding that Houston's diversity goes further than just where people originate from. "Houston has all these pieces put together ... for growing and scaling organizations," she adds.

"I've worked with thousands of students in Houston who are actively looking to better themselves and grow their career post college or post high school and go into the workforce."

— Allie Danziger of Ascent Funding says, adding that Gen Z, which is already entering the workforce, is entrepreneurial and ready to change the world. "Seeing the energy of Houstonians is just thrilling," she adds.

"We're working together in the Houston community. ... There are so many opportunities to collaborate but we need conveners." 

— Stacy Putman of INEOS says, adding that within industry there has been a lack of discussion and collaboration because of competition. But, as she's observing, that's changing thanks to conveners at colleges or at the Greater Houston Partnership.

"The opportunity for Houston is that everybody has to step up to be in some way, shape, or form helping us with this."

— Raj Salhotra of Momentum Education says about supporting the future workforce of Houston, including low-income household students.