Q1 2025: UK Economy Picks Up Speed with Best Growth in a Year

Productivity Measurement Analysis series – UK Q1 2025 by Ruby Watson, Nathan McKeogh and Raquel Ortega-Argilés

General summary and main figures

On the 15^th May 2025, the Office for National Statistics (ONS) released its flash estimate of the UK productivity for the first quarter of 2025 (January – March).  These estimates are based on the quarterly estimates of gross domestic product (GDP) and labour market statistics. The release also includes data for Q4 2024 for sectoral labour productivity.

Labour Force Survey (LFS) estimates indicate output per hour worked increased 2.1% in Q1 compared with pre-pandemic levels. Output per worker was also higher by 1.4% when compared with data for the same period. This productivity growth seen is a result of an “increase in gross value added (GVA) of 4.7% and an increase in hours worked by 2.5% over the period”. It is also worth noting that output per hour worked was lower in Q1 2025 compared to Q1 2024 due to hours worked increasing more than GVA.

Table 1: Flash estimates of labour productivity. UK Quarter 1 (Jan to Mar) 2024 to Q1 2025.

Insights into the Q1 2025 productivity release

As indicated with previous quarterly estimates, the ONS emphasised that they are currently adjusting the weighting of the Labour Force Survey (LFS)  to incorporate updated estimates on population and migration data. ONS has indicated that improvements and revisions are planned throughout 2025 and into 2026, based on the availability of sub-national population projections. These adjustments should be considered when analysing the data and figures produced as it could significantly impact our understanding of the UK’s productivity.

Additionally, due to reduced response rates in the LFS base period for the first quarter of 2024, it is recommended that less weight is placed on the quarter-on-year metric comparisons, and more emphasis given to the comparison to the figures in the pre-pandemic period as they could provide a more stable benchmark, though it might not fully capture recent economic shifts (with sharp declines followed by partial rebounds). The long-term effects on workforce dynamics and business efficiency are still unfolding. Overall, these changes will improve the depth and accuracy of productivity assessments, but they will also require caution when comparing with figures with older datasets.

Sectoral contributions

In terms of sectoral contribution, the construction and ICT industries were the biggest drivers of productivity growth with the largest upwards contributions compared to 2019 (average level). The substantial growth seen in the construction industry (1.1%) was a result of a decrease in the number of hours worked coupled with an increase in GVA, meaning output per hour improved. Compared to 2019, the ICT industry growth (1.1%) has been associated with an increase in GVA.  It has continued its strong upward trajectory benefiting from advancements in AI, cloud computing, and digital services. Other sectors, such as Administrative and support services activities or Professional, scientific and technical activities have seen a surge in productivity as remote work and digital transformation have become more widespread. Output per hour in manufacturing showed slight positive growth, suggesting modest efficiency gains. In contrast, over the same period, the health industry made the largest negative contribution (1.3%). Retail and hospitality in 2019 had stable productivity levels. However, the pandemic-induced shifts in consumer behaviour and labour shortages have led to slower recovery, with businesses adapting through automation and streamlined operations. Wholesale and retail productivity growth remains quite low, indicating stability but not significant improvements.

In order to illustrate these effects, two figures are provided. Figure 1 shows the contribution to output per hour (OPH) growth by industry, with bar widths scaled by the relative size of the industry. Most contracting industries reduced OPH contribution by around 0.2% but human health and social work activities plunged by 1.3%. Among expanding sectors manufacturing; administration and support service activities; and professional, scientific and technical activities each contributed about 0.6%. Overall, expansion ranged from 0.1% to 1.1%. Figure 2 illustrates the industry breakdown in terms of output per hour worked, GVA and hours worked changes in 2024 compared to 2019.

Figure 1: Contribution to growth of output per hour worked by industry, percentage points, 2024 compared with 2019, with width of the bar representing relative size of industry. Data Source: Office of National Statistics, Own elaboration by TPI Productivity Lab

Figure 2: Industry Breakdown: Output per Hour, GVA and Hours worked changes, 2024 compared with 2019. Data Source: Office of National Statistics, TPI Productivity Lab reproduction of Office of National Statistics figure

These trends highlight how shifts in labour allocation and industry-specific dynamics shape overall productivity. The estimates show a clear between-industry effect with an economic shift towards lower-productivity industries, resulting in a negative re-allocation effective for the fifth consecutive quarter. This shift is significant as it indicates a change in the composition of the economy, which can have implications for overall productivity.

The sectoral decomposition effects play a key role in influencing economic policy, as it highlights which industries drive productivity growth and which may require policy intervention. Some potential implications of these figures may emphasise the momentum in investment in high-growth sectors such as construction through infrastructure investment or innovation and technological funding. Digital adoption incentives and supply chain optimisations in wholesale and productivity or optimising workforce allocation in healthcare may be targeted measures to consider for improving sectoral efficiency is the less productive sectors.

Experimental methods

As indicated in the latest ONS release on productivity trends, experimental methods can be used to generate estimates. This includes incorporating Paye As You Earn (PAYE) Real Time Information (RTI) and LFS data sources. RTI data is only available from 2014 Q3 onwards. RTI does not include information on self-employment (SE), therefore LFS self-employment data is appended to RTI data to produce more accurate and comparable estimates.

No adjustment is made for those that are employed but not part of PAYE. Using LFS for self-employed risks double counting so to address this, working proprietors are removed. Working proprietors make up 10% of all self-employed workers and can be understood as self- employed individuals who are employees of their own firm.

Since these methods are experimental, results from these data sources should be used with caution. Compared to the 1.4% growth seen in output per worker using the LFS, RTI data sources indicate a growth of 1.7%. With the LFS, output per hour saw a 2.4% growth but a 2.1% growth using RTI.  These results suggest consistent in the trends over the long term.  Comparisons have been illustrated below in figure 3 and figure 4. Figure 3 and figure 4 show the periods of Q1 2015 to Q1 2019 and Q2 2021 to Q1 2025 side by side. The intermediate period of Q2 2019 to Q1 2021 has been omitted to highlight the differences between the LFS and RTI + SE results without the distorting effects of COVID-19.

Figure 3: OPW calculated using LFS vs RTI + SE QoQ Growth (%) for Q1 2015 – Q1 2019 and Q2 2021 – Q1 2025. Data Source: Office for National Statistics, Own elaboration by TPI Productivity Lab

Figure 4: OPH calculated using LFS vs RTI + SE QoQ growth (%) for Q1 2015 – Q1 2019 and Q2 2021 – Q1 2025. Data Source: Office of National Statistics, Own elaboration by TPI Productivity Lab

Divergence in trend

The effect of the coronavirus pandemic on productivity was relatively short term, with the output per hour rebounding quickly and returning to its long-term trend by late 2021- unlike the sharp and prolonged decline observed during the 2008 recession. Figure 5, which illustrates the trajectory of output per hour, hours worked, and gross value added (GVA) from Q1 2007 highlights this trend. However, while the immediate post-pandemic recovery was strong, recent quarters have shown a deceleration in productivity gains and a modest divergence from the long-run tend, suggesting emerging challenges to sustained productivity growth.

Figure 5: Output per hour worked vs Hours worked vs Gross Value Added for Q1 2025 Flash Estimate data (Q1 2007 =100). Data Source: Office of National Statistics, Own elaboration by TPI Productivity Lab

Discussion

According to the Financial Times, the UK economy expanded by 0.7%, the fastest pace in a year. In March alone, the economy grew by 0.2%. GDP per capita, often used as an indicator for living standards, also increased 0.5% over this period. This growth is particularly significant since it is the first time a GDP figure has been above a Reuters forecast, which was predicted at 0.6% in a poll. Chancellor of the Exchequer Rachel Reeves highlighted this performance as evidence of the UK economy’s strength. The Q1 growth carries added significance for the Labour government, which has made economic growth a key objective since assuming office in July 2024.

However, sustaining this momentum in Q2 may prove challenging due to several factors. First, businesses could face pressure from rising employment taxes and an increase in the minimum wage introduced in April. Secondly, uncertainty surrounds the impact of new tariffs that look effect on the 2^nd of April, with the consequences likely to be reflected in Q2 performance (Reuters).

Reuters also notes how the UK outperformed its G7 peers during this period, as shown in figure 6.

* = Estimated value

Figure 6: Q1 GDP Growth by Country. Data Sources: Office of National Statistics, Eurostat, Japanese Cabinet Office, Statistics Canada, Bureau of Economic Analysis, Own elaboration by TPI Productivity Lab