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Paying respondents, IRS records and other pitches to improve US labor data

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Poor response rates used to compile vital U.S. economic surveys have some pitching an unconventional solution: paying respondents to answer questions.

It’s one of several ways economists have proposed the Bureau of Labor Statistics strengthen its data collection and compilation. Others include allowing it to use certain Internal Revenue Service business records and leaning harder on private data and artificial intelligence.

There’s no simple solution for the statistical agency, which has long been trying to boost waning response rates among households and businesses. Skepticism about the accuracy of government statistics has been festering in recent years, but reached a fever pitch when President Donald Trump fired the head of the BLS this month after the agency said job growth in recent months was dramatically weaker than previously reported.

While many of the possible approaches are unorthodox or costly, and would take months or even years to implement, there’s broad agreement the BLS must consider changes to improve America’s economic data.

Here’s a few of those proposals:

Incentives

Using incentives, including paying cash for participation, may be gaining traction after one of the president’s top economists acknowledged their possible use. It’s not a new idea. Years ago, the government conducted several experiments to determine the impact on responses, and some showed promise, according to a BLS paper.

“I think that we can start thinking about incentive schemes to drive response rates higher,” Stephen Miran, chair of the White House Council of Economic Advisers and Trump’s pick to fill a vacated seat on the Federal Reserve Board of Governors, said Aug. 12 on CNBC.

Still, some economists see risks of sampling bias that favors people who are idle or short of cash. It could also be expensive at a time when Trump is seeking to trim the size of government.

Erica Groshen, the BLS commissioner for four years in the 2010s, worries that incentives could bias the sample of respondents, and they could be problematic if some people are compensated and others aren’t.

Response rates for the BLS household survey, which is used to calculate unemployment and labor force participation, have fallen below 70% since late last year. That’s well below the roughly 90% seen a little more than a decade ago. Each month, about 60,000 households are contacted by telephone or personal visit.

“You’re being contacted by strangers, when everyone hates being contacted by strangers,” said Ron Hetrick, a former BLS economist now with the workforce consulting firm Lightcast. He added that “money would certainly help. Modernization would certainly help.”

The BLS’s monthly survey of businesses, which it uses to estimate job totals, has also seen initial monthly responses slip to less than 60% all too frequently over the past couple of years, the agency’s data show. A decade ago, the first collection rate was close to 80%.

That data, which was at the center of Trump’s frustration earlier this month, appears to also be a focus for his new choice to lead the agency. Before he was picked, EJ Antoni said the BLS should suspend the monthly jobs report “until it is corrected.”

IRS records

Another option that has long been floated to enhance not only the BLS establishment survey, but the statistical system as a whole, would be allowing the agency to use certain IRS business records.

The tax agency collects data about new firms created and employee headcount. Those figures could help the BLS keep track of how many workers are being hired when new businesses start up, and how many are let go when firms shut down, Groshen said.

Estimating payrolls of newly opened — or closed — businesses has always been tricky, but a surge of new business formations during the pandemic recovery only made it harder. Some economists said this so-called “birth-death model” was at the root of a 589,000 downward revision to seasonally adjusted employment counts in the year through March 2024.

Still, allowing BLS to use IRS tax records has been a hard sell on Capitol Hill, where elected representatives and congressional staff “nearly never want to deviate from saying no” to expanding access, Groshen said.

Umbrella agency

A related idea to encouraging greater cooperation within government is creating an economic statistics super-agency. The upshot is that it would allow for a more seamless flow of data between the existing agencies. Currently, a substantial portion of official federal statistics is produced by 13 agencies. That’s at odds with some other countries, including Canada with its Statistics Canada, that have a more centralized approach.

In its budget proposal earlier this year, the Trump administration suggested a smaller step — bring BLS under the Commerce Department with the Census Bureau and the Bureau of Economic Analysis.

Frequent benchmarking

Once a year, the BLS benchmarks its payrolls estimate, which is drawn from monthly surveys of about 121,000 establishments and government agencies, to a more robust count gleaned from state unemployment insurance records.

This process is laborious because the BLS has to gather the unemployment insurance records from all the states. Streamlining collection efforts with states has the potential of producing more accurate national payrolls figures. If the BLS benchmarks its employment figures twice a year, it could improve the nation’s job counts, said William Beach, a former BLS commissioner. He estimates that would cost around $25 million a year.

Alternative data

Given the spread of artificial intelligence and alternative data, many are also pushing for the BLS and other federal agencies to embrace new, more modern collection methods than traditional phone calls and surveys. BLS already uses some third-party data for its monthly consumer price index report, including vehicle prices from J.D. Power. And the Census Bureau has not only tapped alternate data sources but also experimented with satellite imagery.

The process for making job estimates is “obsolete and error-prone,” Ray Dalio, the billionaire founder of hedge fund Bridgewater Associates, said in a post on LinkedIn after Trump dismissed the BLS commissioner. Private estimates “were in fact much better,” he said. Dalio declined to comment or clarify what private data he was referring to when reached by phone afterward.

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Accounting

Global ESG Reporting Standards and Double Materiality Compliance

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Corporate accounting departments face expanding reporting expectations as international sustainability disclosure standards achieve regulatory enforcement across major global jurisdictions. Chief Accounting Officers (CAOs) and corporate controllers are establishing rigorous internal accounting controls to treat Environmental, Social, and Governance (ESG) metrics with the same data precision, auditability, and governance as traditional financial statements.

Regulatory Harmonization Under Global Sustainability Frameworks
The implementation of standardized sustainability reporting frameworks—notably rules established by international sustainability accounting boards—has created unified expectations for public and large private enterprises. Corporations must report standardized metrics covering greenhouse gas emissions (Scope 1, 2, and material Scope 3), energy utilization, workforce demographics, and supply chain governance.

In Europe and other participating international jurisdictions, double materiality principles are mandatory. Under double materiality, organizations must report both how external sustainability risks impact corporate financial performance, and how internal corporate operations affect surrounding environmental and social structures.

Integrating Sustainability Metrics into Core ERP Systems
To provide auditable non-financial data, enterprise organizations are integrating specialized carbon accounting and ESG management platforms directly into core ERP systems. Automated data collectors capture energy utility invoices, logistics fuel consumption metrics, and vendor compliance records in real time.

Establishing automated, traceable data pipelines ensures that non-financial reporting is supported by clear audit trails. This structured approach allows external financial auditors to provide reasonable assurance on sustainability disclosures during annual corporate reporting cycles.

Financial Impacts and Capital Market Disclosure
Accurate ESG reporting directly influences corporate cost of capital and institutional credit ratings. Commercial lenders and institutional asset managers systematically incorporate sustainability metrics into risk pricing models. Companies that demonstrate transparent, verifiable progress in operational energy efficiency and climate risk mitigation benefit from expanded access to green bond markets and lower debt pricing.

Action Steps for Accounting Leadership
1. Implement Double Materiality Frameworks: Conduct comprehensive assessments to identify material financial and operational sustainability metrics.
2. Build Auditable Non-Financial Data Pipelines: Automate ESG data collection within core accounting software to ensure data integrity.
3. Align Sustainability with Annual Financial Filings: Prepare non-financial disclosures concurrently with financial statements to satisfy regulatory audit expectations.

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Accounting

Modernizing Internal Controls: Machine Learning and Continuous Monitoring in Auditing

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Internal audit departments and corporate risk managers are modernizing internal control frameworks by shifting from periodic sampling techniques to continuous monitoring and machine learning analytics. As operational data volumes increase across enterprise organizations, automated control testing ensures financial integrity, prevents corporate fraud, and streamlines annual audit engagements.

The Limitation of Periodic Audit Sampling
Historically, internal and external auditors evaluated internal controls by reviewing random samples of financial transactions—often analyzing less than five percent of total ledger entries. In complex enterprise environments, periodic sampling methods carry inherent risks of overlooking localized financial misstatements, unauthorized disbursements, or operational control breakdowns.

In 2026, progressive internal audit functions are utilizing automated continuous monitoring platforms that evaluate one hundred percent of financial transactions in real time. Continuous control auditing systems continuously monitor general ledger entries, procurement approvals, and expense reimbursements across all operating subsidiaries.

AI-Powered Fraud Detection and Anomaly Identification
Machine learning models trained on historical corporate financial data excel at identifying subtle transactional anomalies that indicate potential fraud or operational error. Automated systems instantly flag duplicate invoice payments, unapproved vendor creation, unusual journal entry timing, and unauthorized override of authority thresholds.

When an anomaly is detected, the automated auditing platform generates an instant risk alert, allowing internal audit teams to investigate root causes immediately. Early detection prevents minor operational errors from escalating into material weaknesses in financial reporting.

Streamlining External Audit Preparation
Continuous internal control monitoring delivers significant benefits during annual external financial audits. External audit firms can review continuous audit logs and automated control testing documentation, reducing the time required for manual field testing.

This integrated approach lowers overall audit compliance fees, reduces administrative burdens on corporate accounting staff, and provides senior management and audit committees with real-time visibility into the organization’s overall risk profile.

Core Implementation Guidelines
1. Transition to 100% Data Testing: Replace legacy sampling methods with automated continuous audit monitoring systems.
2. Deploy Anomaly Detection Algorithms: Implement machine learning models to identify unauthorized transactions and operational control overrides.
3. Align Internal and External Audit Workflows: Coordinate continuous control testing protocols with external auditors to optimize annual compliance cycles.

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Accounting

Automated Tax Compliance and Global Regulatory Harmonization in 2026

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Corporate tax accounting departments are navigating an era of unprecedented regulatory complexity as global tax harmonization frameworks take full effect alongside real-time digital tax reporting mandates. Tax directors and accounting teams are adopting cloud-based tax compliance automation tools to manage multi-jurisdictional tax liabilities and satisfy stringent reporting rules across international jurisdictions.

Implementation of Global Minimum Tax Provisions
The implementation of international tax reform agreements—notably the Pillar Two global minimum tax framework—has reshaped multinational corporate tax planning. Multinational enterprises with consolidated revenues exceeding established thresholds must ensure an effective tax rate of at least 15% across every jurisdiction in which they operate.

Accounting teams are implementing specialized tax calculation modules integrated directly into enterprise resource planning (ERP) platforms. These automated tools calculate effective tax rates per country, identify top-up tax liabilities, and generate standardized compliance documentation required by national tax authorities.

Real-Time Digital Invoicing and E-Reporting Mandates
Tax authorities across Europe, Latin America, and Asia-Pacific have enacted mandatory electronic invoicing (e-invoicing) and continuous transaction controls (CTC). Under these systems, corporate transaction data must be submitted electronically to government portals in real time at the point of sale or invoice issuance.

This shift toward continuous digital tax reporting eliminates traditional annual tax audits in favor of ongoing automated compliance monitoring. Accounting departments are upgrading invoicing software to ensure seamless XML data formatting, digital signature authentication, and real-time validation against tax authority databases.

Automation and Data Analytics in Corporate Tax Strategy
To keep pace with dynamic tax legislation, tax departments are transitioning from reactive compliance teams to proactive strategic advisors. Machine learning algorithms analyze corporate transactional data to identify tax credits, research and development (R&D) incentives, and cross-border transfer pricing adjustments.

By automating routine tax return filings and calculations, corporate tax directors can focus on long-term capital structuring, evaluating the tax implications of corporate mergers, and optimizing international supply chain networks.

Strategic Priorities for Tax Executives
1. ERP System Upgrades: Ensure enterprise software is capable of generating real-time, granular tax data required for global minimum tax compliance.
2. E-Invoicing Integration: Implement scalable e-invoicing platforms to satisfy regional continuous transaction control regulations.
3. Strategic Tax Analytics: Utilize predictive tax modeling tools to evaluate structural changes in corporate operations and cross-border trade.

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