Before March 2026, the obstacles to recovery for Lebanon’s fractured economy were Herculean, but not completely hopeless. Standing in the way of reform were entrenched corruption and the ongoing aggression from Israel under the guise of a ceasefire [inlinetweet]following the 2024 conflict which displaced over a million people and inflicted billions in infrastructure damage. [/inlinetweet]Following the February 28 unprovoked US and Israeli attack on Iran, a renewal of that active conflict in Lebanon quickly escalated into a threat scenario where the human costs and infrastructure damage of the past two years could be exceeded and distrust and social tensions brought to new heights.
While the decisions over the new war and its regional escalation could at no time be influenced by the government in Beirut, the potentially world-changing conflict drives home a lesson on the importance of complete sovereignty. Governing a country in compounding crisis requires decisions made quickly, often under pressure, and with incomplete information. Yet Lebanon’s capacity to measure its own economy — to count what it produces, what it owes, who is working, and who is not — has severe limitations. This is a story about what happens when a state in crisis cannot reliably count.
Data collection in Lebanon does not operate through a single integrated system, and not all datasets are systematically published for public access. There is no single centralized platform where all relevant economic data can be accessed in one place. Cooperation generally exists, but standardization, accessibility, and consolidation remain limited. The system functions, yet it relies heavily on administrative effort.
From a public finance perspective, access to information is generally available. Obtaining budgetary and fiscal data often begins with formal requests. “Through my personal experience, never the data was not received,” says Tonia Salameh, economist and data analyst at the Institut des Finances Basil Fuleihan (IOF). “Sometimes the data is received very fast and sometimes not, but we receive it.”
Institutions generally cooperate. The challenge begins after the data arrives.
Rather than flowing through standardized digital systems, information may come in scanned PDFs, non-tabular Excel sheets, or even printed documents requiring manual entry. “Each institution has its own format. There is no unified format that everyone is using,” Salameh explains. “Sometimes we even receive papers, and we do the data entry.”
As a result, analysts spent significant time transforming and cleaning datasets before meaningful analysis can begin. Immediately focusing immediately on interpretation, analysts are required to standardize and reconcile raw data, increasing delays and creating room for inconsistencies. Salameh refers to the underlying administrative and digital infrastructure. “If the system is not available, you can’t gather high-quality data. If the system is old and not everything is automated, how will you gather the data?”
From the private sector perspective, the Chamber of Commerce, Industry and Agriculture of Beirut and Mount Lebanon compile economic reports by drawing from multiple official sources: the Central Administration of Statistics, Banque du Liban, the Ministry of Finance, customs authorities, and international institutions, each operating within its own reporting framework. Executive spoke with two representatives from the Chamber of Commerce who preferred that their responses be attributed to the Chamber as a whole, rather than to be personally identified. “We always get data from the main sources to ensure accuracy,” one representative explains. “But sometimes figures do not match.”
GDP estimates may differ significantly between domestic and international organizations, because of different methodologies. According to one anonymous representative from the Chamber of Commerce, the variance was “around 2 billion dollars” for nominal GDP in 2023 (IMF estimates were $23.6 to 24 billion). Additionally, the growth projection revealed a wide gap, the representative notes: “Even the IMF reports 3.5 percent growth, whereas the government says 5 percent.”
These discrepancies do not necessarily imply manipulation. They reflect methodological differences and the absence of a centralized consolidation and validation mechanism. Without institutional reconciliation, cross-verification becomes the responsibility of external analysts rather than the state itself. Similar challenges appear in labor statistics. Unemployment estimates vary widely across reports ranging from around 30 percent to over 40 percent. Additionally, the most recent comprehensive labor update dates back to 2022.
In agriculture, the Centre de Recherches et d’Études Agricoles Libanais (CREAL) presents a third model, one built on continuous field data collection rather than episodic surveys. “Statistics are continuous,” says Riad Saade, president of CREAL. “That’s the difference.”
CREAL’s system is self-funded and developed over decades. It tracks agricultural production across seasons, regions, and micro-economic variables. “We don’t study a product; we study the season,” Saade explains. Agricultural output varies by region, climate, irrigation methods, and production cycles, making seasonal monitoring more accurate than broad national averages.
CREAL relies on field engineers embedded in local communities to track planted areas, productive areas, yields, irrigation methods, production costs, and farmers’ prices. Data is double-checked and continuously updated, producing a detailed picture of agricultural performance.
Yet when asked whether the Ministry of Agriculture systematically relies on this data for policymaking, Saade’s answer is clear: “No, not at all.” CREAL’s ongoing assessment further suggests that while Lebanon’s agriculture sector has received substantial external funding over the past decades, output has not grown in proportion to that investment. According to Saade, one reason for this is that many projects have not been effectively adapted to the Lebanese context or informed by local data. Instead, they often follow standardized international models led by foreigner project managers.
Across sectors, the pattern is consistent. Data exists. It is collected with effort. It is considered credible. But it is not systematically integrated into policy decisions.
Structural weaknesses beneath the numbers
A deeper constraint lies in digital infrastructure itself. Not all government data is fully digitalized. In some cases, datasets exist but are stored in outdated systems or paper archives. Without full automation, systematic extraction and aggregation become difficult. Lebanon’s statistical challenges extend beyond formatting issues. They reflect deeper structural realities.
A significant share of economic activity operates informally. Businesses remain unregistered. Labor is undeclared. Income is partially unreported. Even the most sophisticated statistical system cannot fully capture activity that escapes formal oversight. “Yes, the share of the informal sector in Lebanon is very high,” IOF’s Salameh acknowledges. “So, part of the data is not available to be analyzed.”
Political instability further disrupts continuity. During years when parliament failed to approve annual budget laws, fiscal reporting lost consistency. “We have data for some years, then not for others,” Salameh explains. “For instance, in 2021 and 2023, the budget law was not approved. We had the draft, but not the law.” Spending continued, but the annual budget was not formally approved by parliament. The issue was not the absence of figures, but the breakdown of institutional rhythm.
Exchange rate volatility added another layer of disruption. During periods of multiple exchange rates, economic values lacked a single reference point. Analysts were forced to calculate currency components separately. “With multi-pricing, you can’t build a strong economy,” a Chamber representative says. Currency inconsistency complicates not only markets but measurement. When prices, wages, and public accounts operate under different benchmarks, statistical comparability weakens.
CREAL raises a different but related critique: the design of donor-funded statistical projects.
“The project managers usually are international staff, and apply the standard methodology by the book,” Saade says. “The project is not usually adapted based on knowledge of Lebanon and its context.” His argument is methodological. Statistical models, he asserts, must reflect local diversity, production patterns, and socio-economic realities rather than rely exclusively on standardized international templates.
Informality, political instability and national insecurity, and exchange rate volatility are constraints that are mutually reinforcing: a large informal economy shrinks the tax base, which weakens institutional capacity, which reduces the quality of statistics, which makes it harder to design policies that bring informal activity into the formal economy.
If data exists, how much does it shape policymaking?
At the IOF, Salameh sees growing demand for evidence-based analysis. “Now there are more requests for data,” she says. “Everyone is realizing that we need evidence-based information to make decisions.” She adds, “Everyone is affected if a decision is not based on facts.”
From the Chamber of Commerce, the tone is less reserved. “If decisions were fully based on figures, we wouldn’t have been in this situation for six years,” said one representative who asked to remain anonymous, referring to the multi-layered economic crisis. At the same time, the Chamber noted that in areas such as port revenue and taxation monitoring, improvements have been planned. Efforts to strengthen revenue collection and reduce leakage show that data and oversight can support specific reforms, particularly in the context of fiscal collapse. However, these improvements remain limited rather than part of a broader systemic change.
Saade had another view. “Decisions are based on either incomplete data or incorrect data.”
The divergence in tone reflects a deeper uncertainty: data may be requested, but its integration into structured policy design remains inconsistent.
When decisions move ahead without reliable measurement, consequences accumulate gradually. Businesses may misjudge investment conditions. Citizens may face poorly adjusted tax or subsidy measures. Public spending may be misallocated. Reform sequencing may weaken. Inaccurate or incomplete data does not isolate risk; it spreads it across the system.
At the same time, economic figures now circulate rapidly in a politically charged digital environment. Salameh notes: “We are in an era of social media and technology, it is very easy for someone to publish any number, and it goes viral whether it is true or not.”
For example, at the beginning of the economic crisis, claims circulated online that Lebanon ranks first globally in gold reserves, a statement later shown to be misleading. While the country holds large gold reserves, it does not rank among the top holders worldwide.
She stresses the importance of verifying sources. Not every figure shared on social media or television can be trusted, and reliable data should be drawn from recognized institutions. Yet accessibility remains uneven. “Not everyone knows where to find these data,” she adds. While official statistics may be published, they are not always easily located or widely communicated to the public.
The Chamber representative agrees that media scope often includes selective or misinterpreted statistics, though he maintains that official figures from recognized institutions remain broadly reliable.
The problem is not necessarily data production. It is interpretation and the absence of consolidation. When multiple figures circulate without clear reconciliation, confusion can replace clarity, even when underlying data is credible.
Beyond counting: What reform requires
Lebanon’s economic challenge is the absence of institutional integration that allows experts to operate and datasets to inform policy. Reform must begin with strengthening the statistical system itself. Ministries and public institutions require harmonized methodologies, standardized digital formats, and predictable publication schedules. Data collection should follow clear institutional mandates rather than depend primarily on temporary projects or external funding. Stable budgets and technical investment are essential for continuity.
Equally important is linking statistical production to structured policy evaluation. Lebanon lacks a permanent macro-fiscal modeling capacity within the government. Major policy decisions including budget proposals, tax measures, subsidy reforms, and public wage adjustments should be assessed against transparent economic projections before implementation. In Lebanon, there is no formal mechanism obliging policymakers to demonstrate that decisions were informed by available evidence. That absence is itself a policy choice.
Institutional leadership must come from the government, particularly through research and statistical authorities. But coordination should extend beyond government. The private sector, research institutions, and specialized agencies should operate within a structured ecosystem where data production, analysis, and policy design are aligned and available for all.
The issue is not only technical. In a country facing overlapping crises and limited control over external shocks, the ability to reliably measure the economy becomes essential for making informed and independent decisions. Without it, decisions are made under pressure without a clear understanding of their consequences.
